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Gupta NS, Kumar P. Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine. Comput Biol Med 2023; 162:107051. [PMID: 37271113 DOI: 10.1016/j.compbiomed.2023.107051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/06/2023] [Accepted: 05/20/2023] [Indexed: 06/06/2023]
Abstract
Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
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Affiliation(s)
- Nancy Sanjay Gupta
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India.
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Changalidis AI, Maksiutenko EM, Barbitoff YA, Tkachenko AA, Vashukova ES, Pachuliia OV, Nasykhova YA, Glotov AS. Aggregation of Genome-Wide Association Data from FinnGen and UK Biobank Replicates Multiple Risk Loci for Pregnancy Complications. Genes (Basel) 2022; 13:genes13122255. [PMID: 36553520 PMCID: PMC9777867 DOI: 10.3390/genes13122255] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/20/2022] [Accepted: 11/23/2022] [Indexed: 12/02/2022] Open
Abstract
Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we collected and analyzed GWAS summary statistics from the FinnGen cohort and UK Biobank for 24 pregnancy complications. In FinnGen, we identified 11 loci associated with pregnancy hypertension, excessive vomiting, and gestational diabetes. When UK Biobank and FinnGen data were combined, we discovered six loci reaching genome-wide significance in the meta-analysis. These include rs35954793 in FGF5 (p=6.1×10-9), rs10882398 in PLCE1 (p=8.9×10-9), and rs167479 in RGL3 (p=5.2×10-9) for pregnancy hypertension, rs10830963 in MTNR1B (p=4.5×10-41) and rs36090025 in TCF7L2 (p=3.4×10-15) for gestational diabetes, and rs2963457 in the EBF1 locus (p=6.5×10-9) for preterm birth. In addition to the identified genome-wide associations, we also replicated 14 out of 40 previously reported GWAS markers for pregnancy complications, including four more preeclampsia-related variants. Finally, annotation of the GWAS results identified a causal relationship between gene expression in the cervix and gestational hypertension, as well as both known and previously uncharacterized genetic correlations between pregnancy complications and other traits. These results suggest new prospects for research into the etiology and pathogenesis of pregnancy complications, as well as early risk prediction for these disorders.
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Affiliation(s)
- Anton I. Changalidis
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Faculty of Software Engineering and Computer Systems, ITMO University, 197101 St. Petersburg, Russia
| | - Evgeniia M. Maksiutenko
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Dpt. of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
| | - Yury A. Barbitoff
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Dpt. of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
- Correspondence: (Y.A.B.); (A.S.G.)
| | - Alexander A. Tkachenko
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Elena S. Vashukova
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Olga V. Pachuliia
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Yulia A. Nasykhova
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Andrey S. Glotov
- Dpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Correspondence: (Y.A.B.); (A.S.G.)
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Lyu J, Groeger JA, Barnett AL, Li H, Wang L, Zhang J, Du W, Hua J. Associations between gestational age and childhood sleep: a national retrospective cohort study. BMC Med 2022; 20:253. [PMID: 35934710 PMCID: PMC9358861 DOI: 10.1186/s12916-022-02443-9] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 06/16/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Both sleep quality and quantity are essential for normal brain development throughout childhood; however, the association between preterm birth and sleep problems in preschoolers is not yet clear, and the effects of gestational age across the full range from preterm to post-term have not been examined. Our study investigated the sleep outcomes of children born at very-preterm (<31 weeks), moderate-preterm (32-33 weeks), late-preterm (34-36 weeks), early-term (37-38 weeks), full-term (39-40 weeks), late-term (41 weeks) and post-term (>41 weeks). METHODS A national retrospective cohort study was conducted with 114,311 children aged 3-5 years old in China. Children's daily sleep hours and pediatric sleep disorders defined by the Children's Sleep Habits Questionnaire (CSHQ) were reported by parents. Linear regressions and logistic regression models were applied to examine gestational age at birth with the sleep outcomes of children. RESULTS Compared with full-term children, a significantly higher CSHQ score, and hence worse sleep, was observed in very-preterm (β = 1.827), moderate-preterm (β = 1.409), late-preterm (β = 0.832), early-term (β = 0.233) and post-term (β = 0.831) children, all p<0.001. The association of pediatric sleep disorder (i.e. CSHQ scores>41) was also seen in very-preterm (adjusted odds ratio [AOR] = 1.287 95% confidence interval [CI] (1.157, 1.433)), moderate-preterm (AOR = 1.249 95% CI (1.110, 1.405)), late-preterm (AOR = 1.111 95% CI (1.052, 1.174)) and post-term (AOR = 1.139 95% CI (1.061, 1.222)), all p<0.001. Shorter sleep duration was also found in very-preterm (β = -0.303), moderate-preterm (β = -0.282), late-preterm (β = -0.201), early-term (β = -0.068) and post-term (β = -0.110) compared with full-term children, all p<0.01. Preterm and post-term-born children had different sleep profiles as suggested by subscales of the CSHQ. CONCLUSIONS Every degree of premature, early-term and post-term birth, compared to full-term, has an association with sleep disorders and shortened daily sleep duration. Preterm, early-term, and post-term should therefore all be monitored with an increased threat of sleep disorder that requires long-term monitoring for adverse sleep outcomes in preschoolers.
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Affiliation(s)
- Jiajun Lyu
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 2699 Gaoke Road, Shanghai, China
| | - John A Groeger
- NTU Psychology, Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, UK
| | - Anna L Barnett
- Centre for Psychological Research, Oxford Brookes University, Oxford, UK
| | - Haifeng Li
- Department of Rehabilitation, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Zhejiang, China
| | - Lei Wang
- Maternal and Child Health Care Hospital of Yangzhou, Affiliated Hospital of Medical College Yangzhou University, Jiangsu, China
| | - Jiajia Zhang
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 2699 Gaoke Road, Shanghai, China
| | - Wenchong Du
- NTU Psychology, Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, UK.
| | - Jing Hua
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 2699 Gaoke Road, Shanghai, China.
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Genetic variation as a long-distance modulator of RAD21 expression in humans. Sci Rep 2022; 12:13035. [PMID: 35906355 PMCID: PMC9338076 DOI: 10.1038/s41598-022-15081-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 06/17/2022] [Indexed: 11/08/2022] Open
Abstract
Somatic mutations and changes in expression of RAD21 are common in many types of cancer. Moreover, sub-optimal levels of RAD21 expression in early development can result in cohesinopathies. Altered RAD21 levels can result directly from mutations in the RAD21 gene. However, whether DNA variants outside of the RAD21 gene could control its expression and thereby contribute to cancer and developmental disease is unknown. In this study, we searched for genomic variants that modify RAD21expression to determine their potential to contribute to development or cancer by RAD21 dysregulation. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes (AARD, AKAP11, GRID1, KCNIP4, RCN1, TRIOBP, and USP32), enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions influencing cancer onset and a potential for diagnostics.
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Tang J, Gou W, Fu Y, Li K, Guo X, Huang T, Liu H, Li D, Zheng JS. Association between postterm pregnancy and adverse growth outcomes in preschool-age children. Am J Clin Nutr 2022; 116:482-490. [PMID: 35544281 PMCID: PMC9348988 DOI: 10.1093/ajcn/nqac127] [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: 12/14/2021] [Accepted: 05/05/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Postterm pregnancy has been associated with higher risk of perinatal mortality and morbidity, but its long-term health effects on offspring are poorly understood. OBJECTIVES The aim of the study was to investigate the prospective associations between maternal postterm pregnancy and adverse growth outcomes in children. METHODS The Jiaxing Birth Cohort is part of a large population-based health surveillance system in China and recruited pregnant females resident in the Jiaxing area between 1999 and 2013; newborns were followed up for a median duration of 5.8 y until they went to school. Mother-child pairs with maternal gestational information and offspring's anthropometric data at 4-7 y old were included. Postterm pregnancy was defined as maternal gestational age ≥42 and <47 wk, and its associations with offspring obesity, overweight/obesity, and thinness during childhood were determined by using Poisson regression models. RESULTS Of the 101,505 included mother-child pairs, 2369 (2.3%) children were born at postterm. Children born at postterm had significantly lower BMI-for-age z score, weight-for-age z score, and height-for-age z score than those born at term; the mean difference (95% CI) was -0.11 (-0.15, -0.06), -0.17 (-0.21, -0.13), and -0.16 (-0.20, -0.12), respectively. When comparing postterm with term pregnancy, the multivariable-adjusted RRs and 95% CIs among preschool-age children were 0.87 (0.68, 1.11) for obesity, 0.82 (0.72, 0.94) for overweight/obesity, and 1.18 (1.09, 1.28) for thinness, respectively. These risk estimates were robust in sensitivity analyses, but were attenuated in several subgroups stratified by age, sex, mode of delivery, and fetal distress. CONCLUSIONS Postterm pregnancy was associated with a higher risk of thinness, and a lower risk of overweight/obesity, as well as lower growth parameters in preschool-age children. These findings imply that postterm pregnancy may impede the long-term growth of offspring.
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Affiliation(s)
- Jun Tang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Kelei Li
- Institute of Nutrition and Health, Qingdao University, Qingdao, China
| | - Xiaofei Guo
- Institute of Nutrition and Health, Qingdao University, Qingdao, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Huijuan Liu
- Jiaxing University Affiliated Women and Children Hospital, Jiaxing, China
| | - Duo Li
- Address correspondence to DL (e-mail: )
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Kryst Ł, Żegleń M, Woronkowicz A, Kowal M. Body composition of children with different gestation time. Am J Hum Biol 2021; 34:e23696. [PMID: 34726810 DOI: 10.1002/ajhb.23696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/01/2021] [Accepted: 10/24/2021] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVES To examine the differences in body composition between prepubescent children, depending on the time of gestation. METHODS The study was conducted among children aged 3-10 years. The thickness of 5 (triceps, subscapular, suprailiac, abdominal, calf) skinfolds, mid-upper arm circumference, body height, weight and femur breadth was measured. Sum of 3 skinfolds, Body Mass Index (BMI) and muscle mass were calculated. Gestation time was obtained using a questionnaire. RESULTS Children in the short gestation time category were generally characterized by the greatest values of the analyzed characteristics, particularly above the ages of 6-8 years. Femur breadth and muscle mass were similar up to the mentioned age in all of the gestation time categories. BMI and all of the adiposity characteristics, below the age of 6 years, were the greatest in the long gestation time category. CONCLUSIONS Results of the present study are important, as excess body mass and adiposity are associated with increased risk of cardiovascular and metabolic abnormalities later in life. Special emphasis should be placed on the prevention of overweight and obesity among premature babies and the education of their parents.
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Affiliation(s)
- Łukasz Kryst
- Department of Anthropology, Faculty of Physical Education and Sport, University of Physical Education in Kraków, Kraków, Poland
| | | | - Agnieszka Woronkowicz
- Department of Anthropology, Faculty of Physical Education and Sport, University of Physical Education in Kraków, Kraków, Poland
| | - Małgorzata Kowal
- Department of Anthropology, Faculty of Physical Education and Sport, University of Physical Education in Kraków, Kraków, Poland
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Schierding W, Horsfield JA, O'Sullivan JM. Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways. J Med Genet 2021; 58:534-542. [PMID: 32917770 PMCID: PMC8327319 DOI: 10.1136/jmedgenet-2020-107095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 06/08/2020] [Accepted: 06/20/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND The cohesin complex plays an essential role in genome organisation and cell division. A full complement of the cohesin complex and its regulators is important for normal development, since heterozygous mutations in genes encoding these components can be sufficient to produce a disease phenotype. The implication that genes encoding the cohesin subunits or cohesin regulators must be tightly controlled and resistant to variability in expression has not yet been formally tested. METHODS Here, we identify spatial-regulatory connections with potential to regulate expression of cohesin loci (Mitotic: SMC1A, SMC3, STAG1, STAG2, RAD21/RAD21-AS; Meiotic: SMC1B, STAG3, REC8, RAD21L1), cohesin-ring support genes (NIPBL, MAU2, WAPL, PDS5A, PDS5B) and CTCF, including linking their expression to that of other genes. We searched the genome-wide association studies (GWAS) catalogue for SNPs mapped or attributed to cohesin genes by GWAS (GWAS-attributed) and the GTEx catalogue for SNPs mapped to cohesin genes by cis-regulatory variants in one or more of 44 tissues across the human body (expression quantitative trail locus-attributed). RESULTS Connections that centre on the cohesin ring subunits provide evidence of coordinated regulation that has little tolerance for perturbation. We used the CoDeS3D SNP-gene attribution methodology to identify transcriptional changes across a set of genes coregulated with the cohesin loci that include biological pathways such as extracellular matrix production and proteasome-mediated protein degradation. Remarkably, many of the genes that are coregulated with cohesin loci are themselves intolerant to loss-of-function. CONCLUSIONS The results highlight the importance of robust regulation of cohesin genes and implicate novel pathways that may be important in the human cohesinopathy disorders.
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Affiliation(s)
| | - Julia A Horsfield
- Department of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, Hampshire, UK
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Rokas A, Mesiano S, Tamam O, LaBella A, Zhang G, Muglia L. Developing a theoretical evolutionary framework to solve the mystery of parturition initiation. eLife 2020; 9:e58343. [PMID: 33380346 PMCID: PMC7775106 DOI: 10.7554/elife.58343] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 12/08/2020] [Indexed: 11/13/2022] Open
Abstract
Eutherian mammals have characteristic lengths of gestation that are key for reproductive success, but relatively little is known about the processes that determine the timing of parturition, the process of birth, and how they are coordinated with fetal developmental programs. This issue remains one of biology's great unsolved mysteries and has significant clinical relevance because preterm birth is the leading cause of infant and under 5 year old child mortality worldwide. Here, we consider the evolutionary influences and potential signaling mechanisms that maintain or end pregnancy in eutherian mammals and use this knowledge to formulate general theoretical evolutionary models. These models can be tested through evolutionary species comparisons, studies of experimental manipulation of gestation period and birth timing, and human clinical studies. Understanding how gestation time and parturition are determined will shed light on this fundamental biological process and improve human health through the development of therapies to prevent preterm birth.
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Affiliation(s)
- Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, United States
| | - Sam Mesiano
- Department of Reproductive Biology, Case Western Reserve University and Department of Obstetrics and Gynecology, University Hospitals of Cleveland, Cleveland, United States
| | - Ortal Tamam
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben Gurion University, Beer Sheva, Israel
| | - Abigail LaBella
- Department of Biological Sciences, Vanderbilt University, Nashville, United States
| | - Ge Zhang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center and Department of Pediatrics. University of Cincinnati College of Medicine, Cincinnati, United States
| | - Louis Muglia
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center and Department of Pediatrics. University of Cincinnati College of Medicine, Cincinnati, United States
- Burroughs Wellcome Fund, Research Triangle Park, Durham, United States
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Parviainen R, Skarp S, Korhonen L, Serlo W, Männikkö M, Sinikumpu JJ. A single genetic locus associated with pediatric fractures: A genome-wide association study on 3,230 patients. Exp Ther Med 2020; 20:1716-1724. [PMID: 32742401 PMCID: PMC7388260 DOI: 10.3892/etm.2020.8885] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 04/29/2020] [Indexed: 12/25/2022] Open
Abstract
The understanding of the biological and environmental risk factors of fractures in pediatrics is limited. Previous studies have reported that fractures involve heritable traits, but the genetic factors contributing to the risk of fractures remain elusive. Furthermore, genetic influences specific to immature bone have not been thoroughly studied. Therefore, the aim of the present study was to identify genetic variations that are associated with fractures in early childhood. The present study used a prospective Northern Finland Birth Cohort (year 1986; n=9,432). The study population was comprised of 3,230 cohort members with available genotype data. A total of 48 members of the cohort (1.5%) had in-hospital treated bone fractures during their first 6 years of life. Furthermore, individuals without fracture (n=3,182) were used as controls. A genome-wide association study (GWAS) was performed using a frequentist association test. In the GWAS analysis, a linear regression model was fitted to test for additive effects of single-nucleotide polymorphisms (SNPs; genotype dosage) adjusting for sex and performing population stratification using genotypic principal components. Using the GWAS analysis, the present study identified one locus with a significant association with fractures during childhood on chromosome 10 (rs112635931) and six loci with a suggested implication. The lead SNP rs112635931 was located near proline- and serine-rich 2 (PROSER2) antisense RNA 1 (PROSER2-AS1) and PROSER2, thus suggesting that these may be novel candidate genes associated with the risk of pediatric fractures.
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Affiliation(s)
- Roope Parviainen
- Department of Children and Adolescents, Oulu Childhood Fracture and Sports Injury Study, Research Unit for Pediatrics, Pediatric Neurology, Pediatric Surgery, Child Psychiatry, Dermatology, Clinical Genetics, Obstetrics and Gynecology, Otorhinolaryngology and Ophthalmology (PEDEGO), Oulu Medical Research Center (MRC), University of Oulu and Oulu University Hospital, FI-90029 Oulu, Finland
| | - Sini Skarp
- Northern Finland Birth Cohort, Faculty of Medicine, University of Oulu, FI-90014 Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, FI-90014 Oulu, Finland
| | - Linda Korhonen
- Department of Children and Adolescents, Oulu Childhood Fracture and Sports Injury Study, Research Unit for Pediatrics, Pediatric Neurology, Pediatric Surgery, Child Psychiatry, Dermatology, Clinical Genetics, Obstetrics and Gynecology, Otorhinolaryngology and Ophthalmology (PEDEGO), Oulu Medical Research Center (MRC), University of Oulu and Oulu University Hospital, FI-90029 Oulu, Finland
| | - Willy Serlo
- Department of Children and Adolescents, Oulu Childhood Fracture and Sports Injury Study, Research Unit for Pediatrics, Pediatric Neurology, Pediatric Surgery, Child Psychiatry, Dermatology, Clinical Genetics, Obstetrics and Gynecology, Otorhinolaryngology and Ophthalmology (PEDEGO), Oulu Medical Research Center (MRC), University of Oulu and Oulu University Hospital, FI-90029 Oulu, Finland
| | - Minna Männikkö
- Northern Finland Birth Cohort, Faculty of Medicine, University of Oulu, FI-90014 Oulu, Finland
| | - Juha-Jaakko Sinikumpu
- Department of Children and Adolescents, Oulu Childhood Fracture and Sports Injury Study, Research Unit for Pediatrics, Pediatric Neurology, Pediatric Surgery, Child Psychiatry, Dermatology, Clinical Genetics, Obstetrics and Gynecology, Otorhinolaryngology and Ophthalmology (PEDEGO), Oulu Medical Research Center (MRC), University of Oulu and Oulu University Hospital, FI-90029 Oulu, Finland
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Lee MA, McMahon G, Karhunen V, Wade KH, Corbin LJ, Hughes DA, Smith GD, Lawlor DA, Jarvelin MR, Timpson NJ. Common variation at 16p11.2 is associated with glycosuria in pregnancy: findings from a genome-wide association study in European women. Hum Mol Genet 2020; 29:2098-2106. [PMID: 32227112 PMCID: PMC7390941 DOI: 10.1093/hmg/ddaa054] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 02/28/2020] [Accepted: 03/25/2020] [Indexed: 01/01/2023] Open
Abstract
Glycosuria is a condition where glucose is detected in urine at higher concentrations than normal (i.e. not detectable). Glycosuria at some point during pregnancy has an estimated prevalence of 50% and is associated with adverse outcomes in both mothers and offspring. Little is currently known about the genetic contribution to this trait or the extent to which it overlaps with other seemingly related traits, e.g. diabetes. We performed a genome-wide association study (GWAS) for self-reported glycosuria in pregnant mothers from the Avon Longitudinal Study of Parents and Children (cases/controls = 1249/5140). We identified two loci, one of which (lead SNP = rs13337037; chromosome 16; odds ratio of glycosuria per effect allele: 1.42; 95% CI: 1.30, 1.56; P = 1.97 × 10-13) was then validated using an obstetric measure of glycosuria measured in the same cohort (227/6639). We performed a secondary GWAS in the 1986 Northern Finland Birth Cohort (NFBC1986; 747/2991) using midwife-reported glycosuria and offspring genotype as a proxy for maternal genotype. The combined results revealed evidence for a consistent effect on glycosuria at the chromosome 16 locus. In follow-up analyses, we saw little evidence of shared genetic underpinnings with the exception of urinary albumin-to-creatinine ratio (Rg = 0.64; SE = 0.22; P = 0.0042), a biomarker of kidney disease. In conclusion, we identified a genetic association with self-reported glycosuria during pregnancy, with the lead SNP located 15kB upstream of SLC5A2, a target of antidiabetic drugs. The lack of strong genetic correlation with seemingly related traits such as type 2 diabetes suggests different genetic risk factors exist for glycosuria during pregnancy.
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Affiliation(s)
- Matthew A Lee
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - George McMahon
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Ville Karhunen
- Faculty of Medicine, School of Public Health, Imperial College London, 156 Norfolk Place, St Mary’s Campus, London W2 1PG, UK
- Faculty of Medicine, Northern Finland Birth Cohort Studies and Center for Life Course Health Research, University of Oulu, Aapistie 5 B, Oulu Fin-902200, Finland
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Laura J Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Marjo-Riitta Jarvelin
- Faculty of Medicine, School of Public Health, Imperial College London, 156 Norfolk Place, St Mary’s Campus, London W2 1PG, UK
- Faculty of Medicine, Northern Finland Birth Cohort Studies and Center for Life Course Health Research, University of Oulu, Aapistie 5 B, Oulu Fin-902200, Finland
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, Avon Longitudinal Study of Parents and Children, Population Health Science, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
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11
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Toppila-Salmi S, Luukkainen AT, Xu B, Lampi J, Auvinen J, Dhaygude K, Järvelin MR, Pekkanen J. Maternal smoking during pregnancy affects adult onset of asthma in offspring: a follow up from birth to age 46 years. Eur Respir J 2020; 55:13993003.01857-2019. [PMID: 32341110 DOI: 10.1183/13993003.01857-2019] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 03/04/2020] [Indexed: 01/17/2023]
Abstract
RATIONALE Environmental tobacco smoke (ETS) exposure increases asthma risk in children. There is limited knowledge of prenatal ETS for adult-onset asthma. OBJECTIVES To determine the association between prenatal ETS and adult onset asthma. MEASUREMENTS AND MAIN RESULTS The questionnaire and clinical data of 5200 people, free of physician-diagnosed asthma by 31 years of age, who were included in the Northern Finland Birth Cohort 1966 Study was used. The association of maternal smoking during the last 3 months of pregnancy with onset of physician-diagnosed asthma and with lung function in adult offspring was studied using adjusted multivariate regression analyses. The cumulative incidence of physician-diagnosed asthma between the ages of 31 and 46 years was 5.1% among men and 8.8% among women. Gestational smoke exposure was associated with adult-onset asthma among offspring (adjusted OR 1.54, 95% CI 1.04-2.29), namely among offspring who reported either past non-diagnosed asthma (OR 9.63, 95% CI 2.28-40.67) or past cough with wheeze (3.21, 95% CI 1.71-6.05). A significant association was detected between gestational smoke exposure and the offspring's forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio at 31 years of age. In offspring with the haplotype rs11702779-AA of RUNX1, gestational smoke exposure was associated with adult-onset asthma (5.53, 95% CI 2.11-14.52, adjusted p-value for interaction 0.10). CONCLUSION Maternal smoking during pregnancy is associated with the cumulative incidence of asthma in offspring between the ages of 31 and 46 years. The association was accentuated in offspring who at age 31, reported having past respiratory problems and/or who had haplotype rs11702779-AA. A reduction in FEV1/FVC ratio was also observed at age 31 years in offspring with gestational smoke exposure. These results could reflect the early vulnerability of offspring's airways to ETS and its putative long-term effects.
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Affiliation(s)
- Sanna Toppila-Salmi
- Medicum, Haartman Institute, University of Helsinki, Helsinki, Finland .,Skin and Allergy Hospital, Helsinki University Hospital, Helsinki, Finland
| | | | - Baizhuang Xu
- Environment Health Unit, National Institute for Health and Welfare, Kuopio, Finland
| | - Jussi Lampi
- Environment Health Unit, National Institute for Health and Welfare, Kuopio, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, Oulu, Finland
| | - Kishor Dhaygude
- Medicum, Haartman Institute, University of Helsinki, Helsinki, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Oulu, Finland.,Imperial College London, London, UK
| | - Juha Pekkanen
- Environment Health Unit, National Institute for Health and Welfare, Kuopio, Finland.,Dep of Public Health, University of Helsinki, Helsinki, Finland
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12
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Fadason T, Schierding W, Kolbenev N, Liu J, Ingram JR, O’Sullivan JM. Reconstructing the blood metabolome and genotype using long-range chromatin interactions. Metabol Open 2020; 6:100035. [PMID: 32812909 PMCID: PMC7424797 DOI: 10.1016/j.metop.2020.100035] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 03/15/2020] [Accepted: 03/16/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND -Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome. OBJECTIVE -We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs. METHOD -We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs. FINDINGS -We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites. CONCLUSIONS -The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels.
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Affiliation(s)
- Tayaza Fadason
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
| | - William Schierding
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
| | - Nikolai Kolbenev
- The Department of Computer Science, The University of Auckland, Auckland, New Zealand
| | - Jiamou Liu
- The Department of Computer Science, The University of Auckland, Auckland, New Zealand
| | | | - Justin M. O’Sullivan
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
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13
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Liu X, Helenius D, Skotte L, Beaumont RN, Wielscher M, Geller F, Juodakis J, Mahajan A, Bradfield JP, Lin FTJ, Vogelezang S, Bustamante M, Ahluwalia TS, Pitkänen N, Wang CA, Bacelis J, Borges MC, Zhang G, Bedell BA, Rossi RM, Skogstrand K, Peng S, Thompson WK, Appadurai V, Lawlor DA, Kalliala I, Power C, McCarthy MI, Boyd HA, Marazita ML, Hakonarson H, Hayes MG, Scholtens DM, Rivadeneira F, Jaddoe VWV, Vinding RK, Bisgaard H, Knight BA, Pahkala K, Raitakari O, Helgeland Ø, Johansson S, Njølstad PR, Fadista J, Schork AJ, Nudel R, Miller DE, Chen X, Weirauch MT, Mortensen PB, Børglum AD, Nordentoft M, Mors O, Hao K, Ryckman KK, Hougaard DM, Kottyan LC, Pennell CE, Lyytikainen LP, Bønnelykke K, Vrijheid M, Felix JF, Lowe WL, Grant SFA, Hyppönen E, Jacobsson B, Jarvelin MR, Muglia LJ, Murray JC, Freathy RM, Werge TM, Melbye M, Buil A, Feenstra B. Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 associate with gestational duration. Nat Commun 2019; 10:3927. [PMID: 31477735 PMCID: PMC6718389 DOI: 10.1038/s41467-019-11881-8] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 08/05/2019] [Indexed: 12/17/2022] Open
Abstract
The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10-14). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.
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Affiliation(s)
- Xueping Liu
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Dorte Helenius
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Line Skotte
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Julius Juodakis
- Department of Obstetrics and Gynecology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Jonathan P Bradfield
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research, LLC, San Diego, CA, USA
| | - Frederick T J Lin
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Mariona Bustamante
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Tarunveer S Ahluwalia
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, NSW, Australia
| | - Jonas Bacelis
- Department of Obstetrics and Gynecology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Maria C Borges
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ge Zhang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA
| | - Bruce A Bedell
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Robert M Rossi
- March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Kristin Skogstrand
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Statens Serum Institut, Center for Neonatal Screening, Department for Congenital Disorders, Copenhagen, Denmark
| | - Shouneng Peng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Wesley K Thompson
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Vivek Appadurai
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Ilkka Kalliala
- Department of Surgery and Cancer, IRDB, Faculty of Medicine, Imperial College, London, W12 0NN, UK
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Haartmaninkatu, 200029 HUS, Finland
| | - Christine Power
- Population, Policy and Practice, Great Ormond Street Institute for Child Health, University College London, London, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, OX3 7LJ, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Heather A Boyd
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral Biology School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Denise M Scholtens
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Fernando Rivadeneira
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rebecca K Vinding
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Hans Bisgaard
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Bridget A Knight
- NIHR Exeter Clinical Research Facility, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland
- Paavo Nurmi Centre, Sports & Exercise Medicine Unit, Department of Health and Physical Activity, University of Turku, 20520, Turku, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20521, Turku, Finland
| | - Øyvind Helgeland
- K. G. Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
- Norwegian Institute of Public Health, Division of Health data and Digitalization, Department of Genetic Research and Bioinformatics, Oslo, Norway
| | - Stefan Johansson
- K. G. Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Pål R Njølstad
- K. G. Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - João Fadista
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Andrew J Schork
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Ron Nudel
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Daniel E Miller
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Xiaoting Chen
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Matthew T Weirauch
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Divisions of Biomedical Informatics and Developmental Biology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Preben Bo Mortensen
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark
| | - Merete Nordentoft
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Mental Health Center Copenhagen, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Kelli K Ryckman
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
- Department of Epidemiology, University of Iowa, Iowa City, IA, USA
| | - David M Hougaard
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Statens Serum Institut, Center for Neonatal Screening, Department for Congenital Disorders, Copenhagen, Denmark
| | - Leah C Kottyan
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, NSW, Australia
| | - Leo-Pekka Lyytikainen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, 33520, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, 33014, Tampere, Finland
| | - Klaus Bønnelykke
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Martine Vrijheid
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - William L Lowe
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Struan F A Grant
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elina Hyppönen
- Population, Policy and Practice, Great Ormond Street Institute for Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Bo Jacobsson
- Department of Obstetrics and Gynecology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
| | - Marjo-Riitta Jarvelin
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Medical Research Council-Health Protection Agency Centre for Environment and Health, Faculty of Medicine, Imperial College London, London, UK
| | - Louis J Muglia
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jeffrey C Murray
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Thomas M Werge
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alfonso Buil
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
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14
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Ho DSW, Schierding W, Wake M, Saffery R, O’Sullivan J. Machine Learning SNP Based Prediction for Precision Medicine. Front Genet 2019; 10:267. [PMID: 30972108 PMCID: PMC6445847 DOI: 10.3389/fgene.2019.00267] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 03/11/2019] [Indexed: 12/17/2022] Open
Abstract
In the past decade, precision genomics based medicine has emerged to provide tailored and effective healthcare for patients depending upon their genetic features. Genome Wide Association Studies have also identified population based risk genetic variants for common and complex diseases. In order to meet the full promise of precision medicine, research is attempting to leverage our increasing genomic understanding and further develop personalized medical healthcare through ever more accurate disease risk prediction models. Polygenic risk scoring and machine learning are two primary approaches for disease risk prediction. Despite recent improvements, the results of polygenic risk scoring remain limited due to the approaches that are currently used. By contrast, machine learning algorithms have increased predictive abilities for complex disease risk. This increase in predictive abilities results from the ability of machine learning algorithms to handle multi-dimensional data. Here, we provide an overview of polygenic risk scoring and machine learning in complex disease risk prediction. We highlight recent machine learning application developments and describe how machine learning approaches can lead to improved complex disease prediction, which will help to incorporate genetic features into future personalized healthcare. Finally, we discuss how the future application of machine learning prediction models might help manage complex disease by providing tissue-specific targets for customized, preventive interventions.
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Affiliation(s)
| | | | - Melissa Wake
- Murdoch Children Research Institute, Melbourne, VIC, Australia
| | - Richard Saffery
- Murdoch Children Research Institute, Melbourne, VIC, Australia
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15
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Majewska M, Lipka A, Paukszto L, Jastrzebski JP, Szeszko K, Gowkielewicz M, Lepiarczyk E, Jozwik M, Majewski MK. Placenta Transcriptome Profiling in Intrauterine Growth Restriction (IUGR). Int J Mol Sci 2019; 20:E1510. [PMID: 30917529 PMCID: PMC6471577 DOI: 10.3390/ijms20061510] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 03/22/2019] [Accepted: 03/24/2019] [Indexed: 12/14/2022] Open
Abstract
Intrauterine growth restriction (IUGR) is a serious pathological complication associated with compromised fetal development during pregnancy. The aim of the study was to broaden knowledge about the transcriptomic complexity of the human placenta by identifying genes potentially involved in IUGR pathophysiology. RNA-Seq data were used to profile protein-coding genes, detect alternative splicing events (AS), single nucleotide variant (SNV) calling, and RNA editing sites prediction in IUGR-affected placental transcriptome. The applied methodology enabled detection of 37,501 transcriptionally active regions and the selection of 28 differentially-expressed genes (DEGs), among them 10 were upregulated and 18 downregulated in IUGR-affected placentas. Functional enrichment annotation indicated that most of the DEGs were implicated in the processes of inflammation and immune disorders related to IUGR and preeclampsia. Additionally, we revealed that some genes (S100A13, GPR126, CTRP1, and TFPI) involved in the alternation of splicing events were mainly implicated in angiogenic-related processes. Significant SNVs were overlapped with 6533 transcripts and assigned to 2386 coding sequence (CDS), 1528 introns, 345 5' untranslated region (UTR), 1260 3'UTR, 918 non-coding RNA (ncRNA), and 10 intergenic regions. Within CDS regions, 543 missense substitutions with functional effects were recognized. Two known mutations (rs4575, synonymous; rs3817, on the downstream region) were detected within the range of AS and DEG candidates: PA28β and PINLYP, respectively. Novel genes that are dysregulated in IUGR were detected in the current research. Investigating genes underlying the IUGR is crucial for identification of mechanisms regulating placental development during a complicated pregnancy.
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Affiliation(s)
- Marta Majewska
- Department of Human Physiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Warszawska Str 30, 10-082 Olsztyn, Poland.
| | - Aleksandra Lipka
- Department of Gynecology and Obstetrics, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Niepodleglosci Str 44, 10-045 Olsztyn, Poland.
| | - Lukasz Paukszto
- Department of Plant Physiology, Genetics and Biotechnology, Faculty of Biology and Biotechnology, University of Warmia and Mazury in Olsztyn, Oczapowskiego Str 1A, 10-719 Olsztyn-Kortowo, Poland.
| | - Jan Pawel Jastrzebski
- Department of Plant Physiology, Genetics and Biotechnology, Faculty of Biology and Biotechnology, University of Warmia and Mazury in Olsztyn, Oczapowskiego Str 1A, 10-719 Olsztyn-Kortowo, Poland.
| | - Karol Szeszko
- Department of Animal Anatomy and Physiology, Faculty of Biology and Biotechnology, University of Warmia and Mazury in Olsztyn, Oczapowskiego Str 1A, 10-719 Olsztyn-Kortowo, Poland.
| | - Marek Gowkielewicz
- Department of Gynecology and Obstetrics, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Niepodleglosci Str 44, 10-045 Olsztyn, Poland.
| | - Ewa Lepiarczyk
- Department of Human Physiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Warszawska Str 30, 10-082 Olsztyn, Poland.
| | - Marcin Jozwik
- Department of Gynecology and Obstetrics, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Niepodleglosci Str 44, 10-045 Olsztyn, Poland.
| | - Mariusz Krzysztof Majewski
- Department of Human Physiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Warszawska Str 30, 10-082 Olsztyn, Poland.
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16
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Fang L, Jiang J, Li B, Zhou Y, Freebern E, Vanraden PM, Cole JB, Liu GE, Ma L. Genetic and epigenetic architecture of paternal origin contribute to gestation length in cattle. Commun Biol 2019; 2:100. [PMID: 30886909 PMCID: PMC6418173 DOI: 10.1038/s42003-019-0341-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 02/06/2019] [Indexed: 12/19/2022] Open
Abstract
The length of gestation can affect offspring health and performance. Both maternal and fetal effects contribute to gestation length; however, paternal contributions to gestation length remain elusive. Using genome-wide association study (GWAS) in 27,214 Holstein bulls with millions of gestation records, here we identify nine paternal genomic loci associated with cattle gestation length. We demonstrate that these GWAS signals are enriched in pathways relevant to embryonic development, and in differentially methylated regions between sperm samples with long and short gestation length. We reveal that gestation length shares genetic and epigenetic architecture in sperm with calving ability, body depth, and conception rate. While several candidate genes are detected in our fine-mapping analysis, we provide evidence indicating ZNF613 as a promising candidate for cattle gestation length. Collectively, our findings support that the paternal genome and epigenome can impact gestation length potentially through regulation of the embryonic development. Lingzhao Fang et al. studied the paternal genetic variants that affect gestational length in cattle. They found that paternal genes from pathways involved in embryonic development were associated with gestation length, and that these were often found in differentially methylated regions of the genome.
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Affiliation(s)
- Lingzhao Fang
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.,Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Jicai Jiang
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Bingjie Li
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, 430070, Wuhan, Hubei, China
| | - Ellen Freebern
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Paul M Vanraden
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD, 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
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17
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Mead TJ, Apte SS. ADAMTS proteins in human disorders. Matrix Biol 2018; 71-72:225-239. [PMID: 29885460 DOI: 10.1016/j.matbio.2018.06.002] [Citation(s) in RCA: 174] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 06/04/2018] [Accepted: 06/05/2018] [Indexed: 02/07/2023]
Abstract
ADAMTS proteins are a superfamily of 26 secreted molecules comprising two related, but distinct families. ADAMTS proteases are zinc metalloendopeptidases, most of whose substrates are extracellular matrix (ECM) components, whereas ADAMTS-like proteins lack a metalloprotease domain, reside in the ECM and have regulatory roles vis-à-vis ECM assembly and/or ADAMTS activity. Evolutionary conservation and expansion of ADAMTS proteins in mammals is suggestive of crucial embryologic or physiological roles in humans. Indeed, Mendelian disorders or birth defects resulting from naturally occurring ADAMTS2, ADAMTS3, ADAMTS10, ADAMTS13, ADAMTS17, ADAMTS20, ADAMTSL2 and ADAMTSL4 mutations as well as numerous phenotypes identified in genetically engineered mice have revealed ADAMTS participation in major biological pathways. Important roles have been identified in a few acquired conditions. ADAMTS5 is unequivocally implicated in pathogenesis of osteoarthritis via degradation of aggrecan, a major structural proteoglycan in cartilage. ADAMTS7 is strongly associated with coronary artery disease and promotes atherosclerosis. Autoantibodies to ADAMTS13 lead to a platelet coagulopathy, thrombotic thrombocytopenic purpura, which is similar to that resulting from ADAMTS13 mutations. ADAMTS proteins have numerous potential connections to other human disorders that were identified by genome-wide association studies. Here, we review inherited and acquired human disorders in which ADAMTS proteins participate, and discuss progress and prospects in therapeutics.
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Affiliation(s)
- Timothy J Mead
- Department of Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44195, United States
| | - Suneel S Apte
- Department of Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44195, United States.
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