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Leite JMRS, Pereira JL, Alves de Souza C, Pavan Soler JM, Mingroni-Netto RC, Fisberg RM, Rogero MM, Sarti FM. Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition. Lipids Health Dis 2024; 23:229. [PMID: 39060932 PMCID: PMC11282745 DOI: 10.1186/s12944-024-02085-1] [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: 11/08/2023] [Accepted: 03/20/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Cardiovascular diseases (CVDs) comprise major causes of death worldwide, leading to extensive burden on populations and societies. Alterations in normal lipid profiles, i.e., dyslipidemia, comprise important risk factors for CVDs. However, there is lack of comprehensive evidence on the genetic contribution to dyslipidemia in highly admixed populations. The identification of single nucleotide polymorphisms (SNPs) linked to blood lipid traits in the Brazilian population was based on genome-wide associations using data from the São Paulo Health Survey with Focus on Nutrition (ISA-Nutrition). METHODS A total of 667 unrelated individuals had genetic information on 330,656 SNPs available, and were genotyped with Axiom™ 2.0 Precision Medicine Research Array. Genetic associations were tested at the 10- 5 significance level for the following phenotypes: low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), high-density lipoprotein cholesterol (HDL-c), HDL-c/LDL-c ratio, triglycerides (TGL), total cholesterol, and non-HDL-c. RESULTS There were 19 significantly different SNPs associated with lipid traits, the majority of which corresponding to intron variants, especially in the genes FAM81A, ZFHX3, PTPRD, and POMC. Three variants (rs1562012, rs16972039, and rs73401081) and two variants (rs8025871 and rs2161683) were associated with two and three phenotypes, respectively. Among the subtypes, non-HDL-c had the highest proportion of associated variants. CONCLUSIONS The results of the present genome-wide association study offer new insights into the genetic structure underlying lipid traits in underrepresented populations with high ancestry admixture. The associations were robust across multiple lipid phenotypes, and some of the phenotypes were associated with two or three variants. In addition, some variants were present in genes that encode ncRNAs, raising important questions regarding their role in lipid metabolism.
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Affiliation(s)
| | | | | | - Júlia M Pavan Soler
- Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil
| | | | - Regina M Fisberg
- School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Marcelo M Rogero
- School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Flavia M Sarti
- School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil.
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2
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Shangguan Q, Yang J, Li B, Chen H, Yang L. Association of the hemoglobin glycation index with cardiovascular and all-cause mortality in individuals with hypertension: findings from NHANES 1999-2018. Front Endocrinol (Lausanne) 2024; 15:1401317. [PMID: 38915892 PMCID: PMC11194314 DOI: 10.3389/fendo.2024.1401317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 05/28/2024] [Indexed: 06/26/2024] Open
Abstract
Background This study examines the association between Hemoglobin Glycation Index (HGI) and the risk of mortality among individuals with hypertension and to explore gender-specific effects. Methods Data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 were analyzed. Three models were constructed to assess the relationship between HGI and mortality risks, controlling for various covariates. Nonlinear relationships were explored using restricted cubic splines (RCS) and threshold effect analysis. Results The findings reveal a U-shaped relationship between HGI and the cardiovascular disease (CVD) and all-cause mortality after adjusting for multiple covariates. Gender- specific analysis indicated a U-shaped relationship in men, with threshold points of -0.271, and 0.115, respectively. Before the threshold point, HGI was negatively associated with CVD mortality (HR: 0.64, 95%CI: 0.44, 0.93, P=0.02) and all-cause mortality (HR: 0.84, 95%CI: 0.71, 0.99), and after the threshold point, HGI was positively associated with CVD mortality (HR: 1.48, 95%CI: 1.23, 1.79, P<0.01) and all-cause mortality (HR: 1.41, 95%CI: 1.24, 1.60). In contrast, HGI had a J-shaped relationship with CVD mortality and a L-shaped relationship with all-cause mortality in females. Before the threshold points, the risk of all-cause mortality decreased (HR: 0.66, 95%CI:0.56, 0.77, P=0.04) and after the threshold points, the risk of CVD mortality increased (HR: 1.39, 95%CI:1.12, 1.72, P<0.01) progressively with increasing HGI. Conclusion The research highlights the significance of maintaining proper HGI levels in individuals with hypertension and validates HGI as a notable indicator of cardiovascular and all-cause mortality risks. It also highlights the significant role of gender in the relationship between HGI and these risks.
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Affiliation(s)
- Qing Shangguan
- Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Jingqi Yang
- Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Bin Li
- Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Huaigang Chen
- Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
- Medical College of Nanchang University, Nanchang, China
| | - Liu Yang
- Department of Cardiology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
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Alser M, Naja K, Elrayess MA. Mechanisms of body fat distribution and gluteal-femoral fat protection against metabolic disorders. Front Nutr 2024; 11:1368966. [PMID: 38590830 PMCID: PMC10999599 DOI: 10.3389/fnut.2024.1368966] [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: 01/11/2024] [Accepted: 03/07/2024] [Indexed: 04/10/2024] Open
Abstract
Obesity is a major health problem that affects millions of individuals, and it is associated with metabolic diseases including insulin resistance (IR), type 2 diabetes (T2D), and cardiovascular diseases (CVDs). However, Body fat distribution (BFD) rather than crude obesity is now considered as a more accurate factor associated with these diseases. The factors affecting BFD vary, from genetic background, epigenetic factors, ethnicity, aging, hormonal changes, to lifestyle and medication consumptions. The main goal of controlling BFD comes from the fact that fat accumulation in different depots has a different effect on the overall health and metabolic health of individuals. It is well established that fat storage in the abdominal visceral depot is associated with metabolic disorder occurrence, while gluteal-femoral subcutaneous fat depot seems to be protective against these diseases. In this paper, we will summarize the factors affecting fat distribution. Then, we will present evidence connecting gluteal-femoral fat depot with protection against metabolic disorders including IR, T2D, and CVDs. Finally, we will list the suggested mechanisms that lead to this protective effect. The abstract is visualized in Graphical Abstract.
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Affiliation(s)
- Maha Alser
- Biomedical Research Center, Qatar University, Doha, Qatar
| | - Khaled Naja
- Biomedical Research Center, Qatar University, Doha, Qatar
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha, Qatar
- QU Health, Qatar University, Doha, Qatar
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4
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Li YL, Zhang Y, Chen N, Yan YX. The role of m 6A modification in type 2 diabetes: A systematic review and integrative analysis. Gene 2024; 898:148130. [PMID: 38181926 DOI: 10.1016/j.gene.2024.148130] [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: 11/02/2023] [Revised: 12/14/2023] [Accepted: 01/02/2024] [Indexed: 01/07/2024]
Abstract
This study focuses on the latest developments in the studies of m6A modification and provides an up-to-date summary of the association between m6A modification and type 2 diabetes (T2D). The possible mechanisms of m6A related to T2D were summarized by literature review. The differentially expressed genes (DEGs) of m6A methylase in T2D were analyzed from 12 datasets in Gene Expression Omnibus (GEO). The associations between m6A level and T2D were explored in four electronic databases, including PubMed, EmBase, Web of Science and CNKI. Standard mean difference (SMD) and 95 % confidence interval (95 %CI) was calculated to assess the total effect in integrative analysis. Differential expression genes detected in at least three of six tissues were ZC3H13, YTHDC1/2, and IGF2BP2. LRPPRC were differentially expressed in five tissues except in arterial tissue. A total of 6 studies were included for integrative analysis. The mean m6A levels were significantly lower in T2D than those in normal controls (SMD = -1.35, 95 %CI: -2.58 to -0.11). This systematic review and integrative analysis summarize the previous studies on the association between m6A modification and T2D and the possible role of m6A modification in the progression of T2D, such as abnormal blood glucose, abnormal pancreatic β-cell function, insulin resistance, and abnormal lipid metabolism. The integrative analysis showed that decreased level of m6A was associated with T2D. These findings provide new targets for early detection and treatment for T2D.
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Affiliation(s)
- Yan-Ling Li
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China; Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - Yu Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China; Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - Ning Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China; Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - Yu-Xiang Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China; Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
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5
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Bojarczuk A, Egorova ES, Dzitkowska-Zabielska M, Ahmetov II. Genetics of Exercise and Diet-Induced Fat Loss Efficiency: A Systematic Review. J Sports Sci Med 2024; 23:236-257. [PMID: 38455434 PMCID: PMC10915602 DOI: 10.52082/jssm.2024.236] [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: 01/08/2024] [Accepted: 02/21/2024] [Indexed: 03/09/2024]
Abstract
Physical exercise and dieting are well-known and effective methods for fat loss and improving cardiovascular health. However, different individuals often react differently to the same exercise regimen or dietary plan. While specific individuals may undergo substantial fat loss, others may observe only limited effects. A wide range of inter-individual variability in weight gain and changes in body composition induced by physical exercises and diets led to an investigation into the genetic factors that may contribute to the individual variations in such responses. This systematic review aimed at identifying the genetic markers associated with fat loss resulting from diet or exercise. A search of the current literature was performed using the PubMed database. Forty-seven articles met the inclusion criteria when assessing genetic markers associated with weight loss efficiency in response to different types of exercises and diets. Overall, we identified 30 genetic markers of fat-loss efficiency in response to different kinds of diets and 24 in response to exercise. Most studies (n = 46) used the candidate gene approach. We should aspire to the customized selection of exercise and dietary plans for each individual to prevent and treat obesity.
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Affiliation(s)
- Aleksandra Bojarczuk
- Faculty of Physical Culture, Gdansk University of Physical Education and Sport, Gdansk, Poland
| | - Emiliya S Egorova
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia
| | | | - Ildus I Ahmetov
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia
- Sports Genetics Laboratory, St Petersburg Research Institute of Physical Culture, St. Petersburg, Russia
- Center for Phygital Education and Innovative Sports Technologies, Plekhanov Russian University of Economics, Moscow, Russia
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
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6
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Mauvais-Jarvis F. Sex differences in energy metabolism: natural selection, mechanisms and consequences. Nat Rev Nephrol 2024; 20:56-69. [PMID: 37923858 DOI: 10.1038/s41581-023-00781-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2023] [Indexed: 11/06/2023]
Abstract
Metabolic homeostasis operates differently in men and women. This sex asymmetry is the result of evolutionary adaptations that enable women to resist loss of energy stores and protein mass while remaining fertile in times of energy deficit. During starvation or prolonged exercise, women rely on oxidation of lipids, which are a more efficient energy source than carbohydrates, to preserve glucose for neuronal and placental function and spare proteins necessary for organ function. Carbohydrate reliance in men could be an evolutionary adaptation related to defence and hunting, as glucose, unlike lipids, can be used as a fuel for anaerobic high-exertion muscle activity. The larger subcutaneous adipose tissue depots in healthy women than in healthy men provide a mechanism for lipid storage. As female mitochondria have higher functional capacity and greater resistance to oxidative damage than male mitochondria, uniparental inheritance of female mitochondria may reduce the transmission of metabolic disorders. However, in women, starvation resistance and propensity to obesity have evolved in tandem, and the current prevalence of obesity is greater in women than in men. The combination of genetic sex, programming by developmental testosterone in males, and pubertal sex hormones defines sex-specific biological systems in adults that produce phenotypic sex differences in energy homeostasis, metabolic disease and drug responses.
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Affiliation(s)
- Franck Mauvais-Jarvis
- Section of Endocrinology and Metabolism, John W. Deming Department of Medicine, Tulane University School of Medicine and Tulane Center of Excellence in Sex-Based Biology & Medicine, New Orleans, LA, USA.
- Endocrine service, Southeast Louisiana Veterans Health Care System, New Orleans, LA, USA.
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7
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Harris HA, Friedman C, Starling AP, Dabelea D, Johnson SL, Fuemmeler BF, Jima D, Murphy SK, Hoyo C, Jansen PW, Felix JF, Mulder RH. An epigenome-wide association study of child appetitive traits and DNA methylation. Appetite 2023; 191:107086. [PMID: 37844693 PMCID: PMC11156223 DOI: 10.1016/j.appet.2023.107086] [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: 06/19/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023]
Abstract
The etiology of childhood appetitive traits is poorly understood. Early-life epigenetic processes may be involved in the developmental programming of appetite regulation in childhood. One such process is DNA methylation (DNAm), whereby a methyl group is added to a specific part of DNA, where a cytosine base is next to a guanine base, a CpG site. We meta-analyzed epigenome-wide association studies (EWASs) of cord blood DNAm and early-childhood appetitive traits. Data were from two independent cohorts: the Generation R Study (n = 1,086, Rotterdam, the Netherlands) and the Healthy Start study (n = 236, Colorado, USA). DNAm at autosomal methylation sites in cord blood was measured using the Illumina Infinium HumanMethylation450 BeadChip. Parents reported on their child's food responsiveness, emotional undereating, satiety responsiveness and food fussiness using the Children's Eating Behaviour Questionnaire at age 4-5 years. Multiple regression models were used to examine the association of DNAm (predictor) at the individual site- and regional-level (using DMRff) with each appetitive trait (outcome), adjusting for covariates. Bonferroni-correction was applied to adjust for multiple testing. There were no associations of DNAm and any appetitive trait when examining individual CpG-sites. However, when examining multiple CpGs jointly in so-called differentially methylated regions, we identified 45 associations of DNAm with food responsiveness, 7 associations of DNAm with emotional undereating, 13 associations of DNAm with satiety responsiveness, and 9 associations of DNAm with food fussiness. This study shows that DNAm in the newborn may partially explain variation in appetitive traits expressed in early childhood and provides preliminary support for early programming of child appetitive traits through DNAm. Investigating differential DNAm associated with appetitive traits could be an important first step in identifying biological pathways underlying the development of these behaviors.
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Affiliation(s)
- Holly A Harris
- Department of Child & Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Erasmus University Rotterdam, Department of Psychology, Education & Child Studies, Rotterdam, the Netherlands.
| | - Chloe Friedman
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Susan L Johnson
- Department of Pediatrics, Section of Nutrition, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Bernard F Fuemmeler
- Virginia Commonwealth University, Massey Comprehensive Cancer Center, Richmond, VA, USA.
| | - Dereje Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
| | - Susan K Murphy
- Duke University Medical Center, Department of Obstetrics and Gynecology, Reproductive Sciences, Durham, NC, USA.
| | - Cathrine Hoyo
- Department of Biological Sciences, Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
| | - Pauline W Jansen
- Department of Child & Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Erasmus University Rotterdam, Department of Psychology, Education & Child Studies, Rotterdam, the Netherlands.
| | - 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.
| | - Rosa H Mulder
- 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.
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8
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Nguyen JP, Arthur TD, Fujita K, Salgado BM, Donovan MKR, Matsui H, Kim JH, D'Antonio-Chronowska A, D'Antonio M, Frazer KA. eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk. Nat Commun 2023; 14:6928. [PMID: 37903777 PMCID: PMC10616100 DOI: 10.1038/s41467-023-42560-4] [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: 01/31/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023] Open
Abstract
The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4065 genes and 4016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages.
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Affiliation(s)
- Jennifer P Nguyen
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Timothy D Arthur
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Kyohei Fujita
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Bianca M Salgado
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Margaret K R Donovan
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Hiroko Matsui
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Ji Hyun Kim
- Department of Pediatrics, Dongguk University Ilsan Hospital, Goyang, South Korea
| | | | - Matteo D'Antonio
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Kelly A Frazer
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.
- Institute of Genomic Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
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Abstract
Obesity is a common complex trait that elevates the risk for various diseases, including type 2 diabetes and cardiovascular disease. A combination of environmental and genetic factors influences the pathogenesis of obesity. Advances in genomic technologies have driven the identification of multiple genetic loci associated with this disease, ranging from studying severe onset cases to investigating common multifactorial polygenic forms. Additionally, findings from epigenetic analyses of modifications to the genome that do not involve changes to the underlying DNA sequence have emerged as key signatures in the development of obesity. Such modifications can mediate the effects of environmental factors, including diet and lifestyle, on gene expression and clinical presentation. This review outlines what is known about the genetic and epigenetic contributors to obesity susceptibility, along with the albeit limited therapeutic options currently available. Furthermore, we delineate the potential mechanisms of actions through which epigenetic changes can mediate environmental influences and the related opportunities they present for future interventions in the management of obesity.
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Affiliation(s)
- Khanh Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Division of Diabetes and Endocrinology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104 USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104 USA
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10
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Chen Y, Du X, Kuppa A, Feitosa MF, Bielak LF, O'Connell JR, Musani SK, Guo X, Kahali B, Chen VL, Smith AV, Ryan KA, Eirksdottir G, Allison MA, Bowden DW, Budoff MJ, Carr JJ, Chen YDI, Taylor KD, Oliveri A, Correa A, Crudup BF, Kardia SLR, Mosley TH, Norris JM, Terry JG, Rotter JI, Wagenknecht LE, Halligan BD, Young KA, Hokanson JE, Washko GR, Gudnason V, Province MA, Peyser PA, Palmer ND, Speliotes EK. Genome-wide association meta-analysis identifies 17 loci associated with nonalcoholic fatty liver disease. Nat Genet 2023; 55:1640-1650. [PMID: 37709864 PMCID: PMC10918428 DOI: 10.1038/s41588-023-01497-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 08/07/2023] [Indexed: 09/16/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is common and partially heritable and has no effective treatments. We carried out a genome-wide association study (GWAS) meta-analysis of imaging (n = 66,814) and diagnostic code (3,584 cases versus 621,081 controls) measured NAFLD across diverse ancestries. We identified NAFLD-associated variants at torsin family 1 member B (TOR1B), fat mass and obesity associated (FTO), cordon-bleu WH2 repeat protein like 1 (COBLL1)/growth factor receptor-bound protein 14 (GRB14), insulin receptor (INSR), sterol regulatory element-binding transcription factor 1 (SREBF1) and patatin-like phospholipase domain-containing protein 2 (PNPLA2), as well as validated NAFLD-associated variants at patatin-like phospholipase domain-containing protein 3 (PNPLA3), transmembrane 6 superfamily 2 (TM6SF2), apolipoprotein E (APOE), glucokinase regulator (GCKR), tribbles homolog 1 (TRIB1), glycerol-3-phosphate acyltransferase (GPAM), mitochondrial amidoxime-reducing component 1 (MARC1), microsomal triglyceride transfer protein large subunit (MTTP), alcohol dehydrogenase 1B (ADH1B), transmembrane channel like 4 (TMC4)/membrane-bound O-acyltransferase domain containing 7 (MBOAT7) and receptor-type tyrosine-protein phosphatase δ (PTPRD). Implicated genes highlight mitochondrial, cholesterol and de novo lipogenesis as causally contributing to NAFLD predisposition. Phenome-wide association study (PheWAS) analyses suggest at least seven subtypes of NAFLD. Individuals in the top 10% and 1% of genetic risk have a 2.5-fold to 6-fold increased risk of NAFLD, cirrhosis and hepatocellular carcinoma. These genetic variants identify subtypes of NAFLD, improve estimates of disease risk and can guide the development of targeted therapeutics.
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Affiliation(s)
- Yanhua Chen
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Xiaomeng Du
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Annapurna Kuppa
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jeffrey R O'Connell
- Department of Endocrinology, Diabetes and Nutrition, University of Maryland - Baltimore, Baltimore, MD, USA
| | - Solomon K Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Bratati Kahali
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - Vincent L Chen
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Kathleen A Ryan
- Department of Endocrinology, Diabetes and Nutrition, University of Maryland - Baltimore, Baltimore, MD, USA
| | | | - Matthew A Allison
- Department of Family Medicine, University of California San Diego, San Diego, CA, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Matthew J Budoff
- Department of Internal Medicine, Lundquist Institute at Harbor-UCLA, Torrance, CA, USA
| | - John Jeffrey Carr
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yii-Der I Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Antonino Oliveri
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Breland F Crudup
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - James G Terry
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian D Halligan
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Kendra A Young
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - John E Hokanson
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - George R Washko
- Department of Medicine, Division of Pulmonary and Critical Care, Brigham and Women's Hospital, Boston, MA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Elizabeth K Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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11
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Kamiza AB, Touré SM, Zhou F, Soremekun O, Cissé C, Wélé M, Touré AM, Nashiru O, Corpas M, Nyirenda M, Crampin A, Shaffer J, Doumbia S, Zeggini E, Morris AP, Asimit JL, Chikowore T, Fatumo S. Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry. Nat Commun 2023; 14:5403. [PMID: 37669986 PMCID: PMC10480211 DOI: 10.1038/s41467-023-41271-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023] Open
Abstract
Most genome-wide association studies (GWAS) for lipid traits focus on the separate analysis of lipid traits. Moreover, there are limited GWASs evaluating the genetic variants associated with multiple lipid traits in African ancestry. To further identify and localize loci with pleiotropic effects on lipid traits, we conducted a genome-wide meta-analysis, multi-trait analysis of GWAS (MTAG), and multi-trait fine-mapping (flashfm) in 125,000 individuals of African ancestry. Our meta-analysis and MTAG identified four and 14 novel loci associated with lipid traits, respectively. flashfm yielded an 18% mean reduction in the 99% credible set size compared to single-trait fine-mapping with JAM. Moreover, we identified more genetic variants with a posterior probability of causality >0.9 with flashfm than with JAM. In conclusion, we identified additional novel loci associated with lipid traits, and flashfm reduced the 99% credible set size to identify causal genetic variants associated with multiple lipid traits in African ancestry.
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Affiliation(s)
- Abram Bunya Kamiza
- The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sounkou M Touré
- The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Feng Zhou
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Opeyemi Soremekun
- The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
| | - Cheickna Cissé
- African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
- Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Mamadou Wélé
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
- Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Aboubacrine M Touré
- Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Oyekanmi Nashiru
- H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | - Manuel Corpas
- School of Life sciences, University of Westminster, London, UK
| | - Moffat Nyirenda
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
| | - Amelia Crampin
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi
| | - Jeffrey Shaffer
- Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Seydou Doumbia
- African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
- Faculty of Medicine and Odonto-stomatology, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Medicine, Translational Genomics, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK
| | | | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Segun Fatumo
- The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
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12
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Glunk V, Laber S, Sinnott-Armstrong N, Sobreira DR, Strobel SM, Batista TM, Kubitz P, Moud BN, Ebert H, Huang Y, Brandl B, Garbo G, Honecker J, Stirling DR, Abdennur N, Calabuig-Navarro V, Skurk T, Ocvirk S, Stemmer K, Cimini BA, Carpenter AE, Dankel SN, Lindgren CM, Hauner H, Nobrega MA, Claussnitzer M. A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes. Nat Metab 2023; 5:861-879. [PMID: 37253881 DOI: 10.1038/s42255-023-00807-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 04/12/2023] [Indexed: 06/01/2023]
Abstract
Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.
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Affiliation(s)
- Viktoria Glunk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Samantha Laber
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Nasa Sinnott-Armstrong
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
- Herbold Computational Biology Program, Publich Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Debora R Sobreira
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Sophie M Strobel
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Thiago M Batista
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Phil Kubitz
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bahareh Nemati Moud
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Hannah Ebert
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Yi Huang
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beate Brandl
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Garrett Garbo
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Julius Honecker
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - David R Stirling
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nezar Abdennur
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Virtu Calabuig-Navarro
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Thomas Skurk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Soeren Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Intestinal Microbiology Research Group, Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Kerstin Stemmer
- Molecular Cell Biology, Institute for Theoretical Medicine, University of Augsburg, Augsburg, Germany
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anne E Carpenter
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Simon N Dankel
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Cecilia M Lindgren
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Hans Hauner
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Marcelo A Nobrega
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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13
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van der Linden EL, Meeks KAC, Chilunga F, Hayfron-Benjamin C, Bahendeka S, Klipstein-Grobusch K, Venema A, van den Born BJ, Agyemang C, Henneman P, Adeyemo A. Epigenome-wide association study of plasma lipids in West Africans: the RODAM study. EBioMedicine 2023; 89:104469. [PMID: 36791658 PMCID: PMC10025759 DOI: 10.1016/j.ebiom.2023.104469] [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: 09/27/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
BACKGROUND DNA-methylation has been associated with plasma lipid concentration in populations of diverse ethnic backgrounds, but epigenome-wide association studies (EWAS) in West-Africans are lacking. The aim of this study was to identify DNA-methylation loci associated with plasma lipids in Ghanaians. METHODS We conducted an EWAS using Illumina 450k DNA-methylation array profiles of extracted DNA from 663 Ghanaian participants. Differentially methylated positions (DMPs) were examined for association with plasma total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, and triglycerides concentrations using linear regression models adjusted for age, sex, body mass index, diabetes mellitus, and technical covariates. Findings were replicated in independent cohorts of different ethnicities. FINDINGS We identified one significantly associated DMP with triglycerides (cg19693031 annotated to TXNIP, regression coefficient beta -0.26, false discovery rate adjusted p-value 0.001), which replicated in-silico in South African Batswana, African American, and European populations. From the top five DMPs with the lowest nominal p-values, two additional DMPs for triglycerides (CPT1A, ABCG1), two DMPs for LDL-cholesterol (EPSTI1, cg13781819), and one for TC (TXNIP) replicated. With the exception of EPSTI1, these loci are involved in lipid transport/metabolism or are known GWAS-associated loci. The top 5 DMPs per lipid trait explained 9.5% in the variance of TC, 8.3% in LDL-cholesterol, 6.1% in HDL-cholesterol, and 11.0% in triglycerides. INTERPRETATION The top DMPs identified in this study are in loci that play a role in lipid metabolism across populations, including West-Africans. Future studies including larger sample size, longitudinal study design and translational research is needed to increase our understanding on the epigenetic regulation of lipid metabolism among West-African populations. FUNDING European Commission under the Framework Programme (grant number: 278901).
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Affiliation(s)
- Eva L van der Linden
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
| | - Karlijn A C Meeks
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Felix Chilunga
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Charles Hayfron-Benjamin
- Department of Physiology, University of Ghana Medical School, Accra, Ghana; Department of Anesthesia and Critical Care, Korle Bu Teaching Hospital, Accra, Ghana
| | | | - Kerstin Klipstein-Grobusch
- Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands; Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Andrea Venema
- Department of Human Genetics, Genome Diagnostics Laboratory Amsterdam, Reproduction & Development, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bert-Jan van den Born
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Peter Henneman
- Department of Human Genetics, Genome Diagnostics Laboratory Amsterdam, Reproduction & Development, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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14
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Functionally Significant Variants in Genes Associated with Abdominal Obesity: A Review. J Pers Med 2023; 13:jpm13030460. [PMID: 36983642 PMCID: PMC10056771 DOI: 10.3390/jpm13030460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/23/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023] Open
Abstract
The high prevalence of obesity and of its associated diseases is a major problem worldwide. Genetic predisposition and the influence of environmental factors contribute to the development of obesity. Changes in the structure and functional activity of genes encoding adipocytokines are involved in the predisposition to weight gain and obesity. In this review, variants in genes associated with adipocyte function are examined, as are variants in genes associated with metabolic aberrations and the accompanying disorders in visceral obesity.
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15
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Yang Y, Zheng Z, Chen Y, Wang X, Wang H, Si Z, Meng R, Wu J. A case control study on the relationship between occupational stress and genetic polymorphism and dyslipidemia in coal miners. Sci Rep 2023; 13:2321. [PMID: 36759651 PMCID: PMC9911731 DOI: 10.1038/s41598-023-29491-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
Dyslipidemia is one of the known risk factors for cardiovascular disease, and its prevalence is increasing worldwide. At present, the study of dyslipidemia has gradually shifted from simple environmental or genetic factors to environment-gene interactions. In order to further explore the etiology and mechanism of dyslipidemia, we used occupational stress(OS) and LYPLAL1, APOC3 and SOD2 gene as research variables to explore their association with dyslipidemia.Here we used a case-control study to include Han workers from a coal mining enterprise in China to determine the association between study variables and dyslipidemia. Monofactor analysis showed that smoking, drinking, physical activity level, DASH diet score, sleep quality, BMI, hypertension, hyperuricemia, shift work, OS were significantly different between the two groups (P < 0.05). In the APOC3 rs2854116 dominant model, patients with CT/CC genotype had a higher risk of dyslipidemia than those with TT genotype. In SOD2 rs4880 recessive model, patients with GG genotype had a lower risk of dyslipidemia than those with AA/AG genotype, and the difference was statistically significant. We found that rs12137855 and OS, rs2854116 and OS, rs4880 and OS had joint effects, but no interaction based on the multiplication and addition model was found (Pinteraction > 0.05). GMDR model showed that the rs12137855-rs2854116-rs4880-OS four-factor model had the highest cross-validation consistency and training-validation accuracy (P < 0.05), suggesting that there was a high-order interaction between them associated with dyslipidemia. We found that dyslipidemia in coal miners was related to OS and genetic factors. Through this study, we revealed the dual regulation of environmental factors and genetic factors on dyslipidemia. At the same time, this study provides clues for understanding the etiology and mechanism of dyslipidemia.
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Affiliation(s)
- Yongzhong Yang
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Ziwei Zheng
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Yuanyu Chen
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Xuelin Wang
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Hui Wang
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Zhikang Si
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Rui Meng
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China
| | - Jianhui Wu
- School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, Hebei, 063210, People's Republic of China. .,Hebei Province Key Laboratory of Occupational Health and Safety for Coal Industry, North China University of Science and Technology, Tangshan, Hebei, People's Republic of China.
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16
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Kentistou KA, Luan J, Wittemans LBL, Hambly C, Klaric L, Kutalik Z, Speakman JR, Wareham NJ, Kendall TJ, Langenberg C, Wilson JF, Joshi PK, Morton NM. Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene. Nat Commun 2023; 14:307. [PMID: 36658113 PMCID: PMC9852585 DOI: 10.1038/s41467-022-35563-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 12/09/2022] [Indexed: 01/20/2023] Open
Abstract
Obesity remains an unmet global health burden. Detrimental anatomical distribution of body fat is a major driver of obesity-mediated mortality risk and is demonstrably heritable. However, our understanding of the full genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. To address this, we impute whole-body imaging adiposity phenotypes in UK Biobank from the 4,366 directly measured participants onto the rest of the cohort, greatly increasing our discovery power. Using these imputed phenotypes in 392,535 participants yielded hundreds of genome-wide significant associations, six of which replicate in independent cohorts. The leading causal gene candidate, ADAMTS14, is further investigated in a mouse knockout model. Concordant with the human association data, the Adamts14-/- mice exhibit reduced adiposity and weight-gain under obesogenic conditions, alongside an improved metabolic rate and health. Thus, we show that phenotypic imputation at scale offers deeper biological insights into the genetics of human adiposity that could lead to therapeutic targets.
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Affiliation(s)
- Katherine A Kentistou
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Laura B L Wittemans
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Catherine Hambly
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Zoltán Kutalik
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, 1010, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - John R Speakman
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
- Centre for Energy Metabolism and Reproduction, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Shenzhen Key Laboratory of Metabolic Health, CAS Centre of Excellence in Animal Evolution and Genetics, Kunming, China
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Timothy J Kendall
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health (BIH) Charité University Medicine, Berlin, Germany
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Nicholas M Morton
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK.
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17
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Streicher SA, Lim U, Park SL, Li Y, Sheng X, Hom V, Xia L, Pooler L, Shepherd J, Loo LWM, Ernst T, Buchthal S, Franke AA, Tiirikainen M, Wilkens LR, Haiman CA, Stram DO, Cheng I, Le Marchand L. Genome-wide association study of abdominal MRI-measured visceral fat: The multiethnic cohort adiposity phenotype study. PLoS One 2023; 18:e0279932. [PMID: 36607984 PMCID: PMC9821421 DOI: 10.1371/journal.pone.0279932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 12/16/2022] [Indexed: 01/07/2023] Open
Abstract
Few studies have explored the genetic underpinnings of intra-abdominal visceral fat deposition, which varies substantially by sex and race/ethnicity. Among 1,787 participants in the Multiethnic Cohort (MEC)-Adiposity Phenotype Study (MEC-APS), we conducted a genome-wide association study (GWAS) of the percent visceral adiposity tissue (VAT) area out of the overall abdominal area, averaged across L1-L5 (%VAT), measured by abdominal magnetic resonance imaging (MRI). A genome-wide significant signal was found on chromosome 2q14.3 in the sex-combined GWAS (lead variant rs79837492: Beta per effect allele = -4.76; P = 2.62 × 10-8) and in the male-only GWAS (lead variant rs2968545: (Beta = -6.50; P = 1.09 × 10-9), and one suggestive variant was found at 13q12.11 in the female-only GWAS (rs79926925: Beta = 6.95; P = 8.15 × 10-8). The negatively associated variants were most common in European Americans (T allele of rs79837492; 5%) and African Americans (C allele of rs2968545; 5%) and not observed in Japanese Americans, whereas the positively associated variant was most common in Japanese Americans (C allele of rs79926925, 5%), which was all consistent with the racial/ethnic %VAT differences. In a validation step among UK Biobank participants (N = 23,699 of mainly British and Irish ancestry) with MRI-based VAT volume, both rs79837492 (Beta = -0.026, P = 0.019) and rs2968545 (Beta = -0.028, P = 0.010) were significantly associated in men only (n = 11,524). In the MEC-APS, the association between rs79926925 and plasma sex hormone binding globulin levels reached statistical significance in females, but not in males, with adjustment for total adiposity (Beta = -0.24; P = 0.028), on the log scale. Rs79837492 and rs2968545 are located in intron 5 of CNTNAP5, and rs79926925, in an intergenic region between GJB6 and CRYL1. These novel findings differing by sex and racial/ethnic group warrant replication in additional diverse studies with direct visceral fat measurements.
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Affiliation(s)
- Samantha A. Streicher
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Unhee Lim
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - S. Lani Park
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Yuqing Li
- Department of Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, California, United States of America
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Victor Hom
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Lucy Xia
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loreall Pooler
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - John Shepherd
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Lenora W. M. Loo
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Thomas Ernst
- University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Steven Buchthal
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Adrian A. Franke
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Maarit Tiirikainen
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Lynne R. Wilkens
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Daniel O. Stram
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, California, United States of America
| | - Loïc Le Marchand
- University of Hawaii Cancer Center, University of Hawaii at Mānoa, Honolulu, Hawaii, United States of America
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18
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Littleton SH, Grant SFA. Strategies to identify causal common genetic variants and corresponding effector genes for paediatric obesity. Pediatr Obes 2022; 17:e12968. [PMID: 35971868 DOI: 10.1111/ijpo.12968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 07/24/2022] [Accepted: 08/01/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Childhood obesity rates are on the rise, but there are currently no effective therapies available to slow or halt their progression. Although environmental and lifestyle factors have been implicated in its pathogenesis, childhood obesity is considered a complex disorder with a clear genetic component. Intense genome-wide association study (GWAS) efforts through large-scale collaborations have enabled the discovery of genetic loci robustly associated with childhood obesity beyond the classic FTO locus. That said, GWAS itself does not pinpoint the actual underlying causal effector genes, but rather just yields association signals in the genome. OBJECTIVE This review aims to outline what has been elucidated thus far on the genetic aetiology of commong childhood obesity and to describe strategies to identify and validate both causal common genetic variants and their corresponding effector genes. RESULTS Relevant cell types for molecular studies can be identified by gene set enrichment analysis and considering known biology of obesity-related physiological processes. Putatively causal single nucleotide polymorphisms (SNPs) can be identified by several methods including statistical fine mapping and 'assay for transposase accessible chromatin sequencing' (ATAC-seq). Variant to gene mapping can then nominate effector genes likely regulated by cis-regulatory elements harbouring putatively causal SNPs. A SNP's cis-regulatory activity can be functionally validated by several in vitro methods including luciferase assay and CRISPR approaches. These CRISPR approaches can also be used to investigate how dysregulatn of effector genes may confer obesity risk. CONCLUSION Uncovering the causative genes related to GWAS signals and elucidating their functional contributions to paediatric obesity with these strategies will deepen our understanding of this disease and serve better treatment outcomes.
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Affiliation(s)
- Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, USA.,Cell and Molecular Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA.,Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, USA.,Divisons of Genetics and Endocrinology, Children's Hospital of Philadelphia, Philadelphia, USA.,Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
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19
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Yam P, VerHague M, Albright J, Gertz E, Pardo-Manuel de Villena F, Bennett BJ. Altered macronutrient composition and genetics influence the complex transcriptional network associated with adiposity in the Collaborative Cross. GENES & NUTRITION 2022; 17:13. [PMID: 35945490 PMCID: PMC9364539 DOI: 10.1186/s12263-022-00714-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 07/04/2022] [Indexed: 11/10/2022]
Abstract
Background Obesity is a serious disease with a complex etiology characterized by overaccumulation of adiposity resulting in detrimental health outcomes. Given the liver’s critical role in the biological processes that attenuate adiposity accumulation, elucidating the influence of genetics and dietary patterns on hepatic gene expression is fundamental for improving methods of obesity prevention and treatment. To determine how genetics and diet impact obesity development, mice from 22 strains of the genetically diverse recombinant inbred Collaborative Cross (CC) mouse panel were challenged to either a high-protein or high-fat high-sucrose diet, followed by extensive phenotyping and analysis of hepatic gene expression. Results Over 1000 genes differentially expressed by perturbed dietary macronutrient composition were enriched for biological processes related to metabolic pathways. Additionally, over 9000 genes were differentially expressed by strain and enriched for biological process involved in cell adhesion and signaling. Weighted gene co-expression network analysis identified multiple gene clusters (modules) associated with body fat % whose average expression levels were influenced by both dietary macronutrient composition and genetics. Each module was enriched for distinct types of biological functions. Conclusions Genetic background affected hepatic gene expression in the CC overall, but diet macronutrient differences also altered expression of a specific subset of genes. Changes in macronutrient composition altered gene expression related to metabolic processes, while genetic background heavily influenced a broad range of cellular functions and processes irrespective of adiposity. Understanding the individual role of macronutrient composition, genetics, and their interaction is critical to developing therapeutic strategies and policy recommendations for precision nutrition. Supplementary Information The online version contains supplementary material available at 10.1186/s12263-022-00714-x.
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20
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Exploring the Genetic Association between Obesity and Serum Lipid Levels Using Bivariate Methods. Twin Res Hum Genet 2022; 25:234-244. [PMID: 36606461 DOI: 10.1017/thg.2022.39] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
It is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.
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21
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Qin X, Chiang CWK, Gaggiotti OE. Deciphering signatures of natural selection via deep learning. Brief Bioinform 2022; 23:6686736. [PMID: 36056746 PMCID: PMC9487700 DOI: 10.1093/bib/bbac354] [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: 05/19/2022] [Revised: 07/11/2022] [Accepted: 07/28/2022] [Indexed: 11/12/2022] Open
Abstract
Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning-based framework, DeepGenomeScan, which can detect signatures of spatially varying selection. We demonstrate that DeepGenomeScan outperformed principal component analysis- and redundancy analysis-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under nonlinear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified by SPA, iHS, Fst and Bayenv when applied to the same dataset.
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Affiliation(s)
- Xinghu Qin
- Centre for Biological Diversity, Sir Harold Mitchell Building, University of St Andrews, Fife, KY16 9TF, UK
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine & Department of Quantitative and Computational Biology, University of Southern California, USA
| | - Oscar E Gaggiotti
- Centre for Biological Diversity, Sir Harold Mitchell Building, University of St Andrews, Fife, KY16 9TF, UK
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22
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Clusters of risk factors in metabolic syndrome and their influence on central blood pressure in a global study. Sci Rep 2022; 12:14409. [PMID: 36002468 PMCID: PMC9402529 DOI: 10.1038/s41598-022-18094-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 08/05/2022] [Indexed: 11/12/2022] Open
Abstract
The effect of metabolic syndrome (MetS) and clusters of its components on central blood pressure (CBP) has not been well characterized. We aimed to describe the effect of MetS and clusters of its components on CBP in a large population and to identify whether this effect differs in men and women. We studied 15,609 volunteers (43% women) from 10 cohorts worldwide who participated in the Metabolic syndrome and Artery REsearch Consortium. MetS was defined according to the NCEP-ATP III criteria (GHTBW, glucose, high-density lipoprotein cholesterol, triglyceride, blood pressure, waist circumference). CBP was measured noninvasively and acquired from pulse wave analysis by applanation tonometry. MetS was associated with a 50% greater odds of having higher CSBP. After controlling for age, male sex, non HDL cholesterol, diabetes mellitus, and mean arterial pressure, only specific clusters of MetS components were associated with a higher CSBP; and some of them were significant in women but not in men. We identified “risky clusters” of MetS variables associated with high CSBP. Future studies are needed to confirm they identify subjects at high risk of accelerated arterial aging and, thus, need more intensive clinical management.
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23
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Li H, Konja D, Wang L, Wang Y. Sex Differences in Adiposity and Cardiovascular Diseases. Int J Mol Sci 2022; 23:ijms23169338. [PMID: 36012601 PMCID: PMC9409326 DOI: 10.3390/ijms23169338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/11/2022] [Accepted: 08/17/2022] [Indexed: 11/16/2022] Open
Abstract
Body fat distribution is a well-established predictor of adverse medical outcomes, independent of overall adiposity. Studying body fat distribution sheds insights into the causes of obesity and provides valuable information about the development of various comorbidities. Compared to total adiposity, body fat distribution is more closely associated with risks of cardiovascular diseases. The present review specifically focuses on the sexual dimorphism in body fat distribution, the biological clues, as well as the genetic traits that are distinct from overall obesity. Understanding the sex determinations on body fat distribution and adiposity will aid in the improvement of the prevention and treatment of cardiovascular diseases (CVD).
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24
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Agrawal S, Wang M, Klarqvist MDR, Smith K, Shin J, Dashti H, Diamant N, Choi SH, Jurgens SJ, Ellinor PT, Philippakis A, Claussnitzer M, Ng K, Udler MS, Batra P, Khera AV. Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nat Commun 2022; 13:3771. [PMID: 35773277 PMCID: PMC9247093 DOI: 10.1038/s41467-022-30931-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/25/2022] [Indexed: 12/11/2022] Open
Abstract
For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as an important modulator of fat distribution. Local adiposity traits (1) highlight depot-specific genetic architecture and (2) enable construction of depot-specific polygenic scores that have divergent associations with type 2 diabetes and coronary artery disease. These results - using MRI-derived, BMI-independent measures of local adiposity - confirm fat distribution as a highly heritable trait with important implications for cardiometabolic health outcomes.
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Affiliation(s)
- Saaket Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Minxian Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | | | - Kirk Smith
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Joseph Shin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hesam Dashti
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nathaniel Diamant
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Seung Hoan Choi
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Sean J Jurgens
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anthony Philippakis
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Melina Claussnitzer
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kenney Ng
- Center for Computational Health, IBM Research, Cambridge, MA, USA
| | - Miriam S Udler
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Verve Therapeutics, Cambridge, MA, USA.
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25
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Yue K, Liu Z, Pi Z, Li H, Wang Y, Song F, Liu Z. Network Pharmacology Combined with Metabolomics Approach to Investigate the Toxicity Mechanism of Paclobutrazol. Chem Res Toxicol 2022; 35:626-635. [PMID: 35298131 DOI: 10.1021/acs.chemrestox.1c00404] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Paclobutrazol (PBZ) is a commonly used plant growth regulator (PGR) with good antibacterial activity. It has widespread applications in agricultural production. However, there is limited research reported on the potential risks of human health resulting from PBZ residues. In this study, using Sprague-Dawley rats, we carried out a systematic study on the hepatotoxicity and nephrotoxicity of PBZ in different doses (0.2, 0.5, and 1.0 g/kg). The metabolic profiles and network pharmacology were combined to construct a PBZ-endogenous substances-gene-hepatorenal diseases network to elucidate the underlying mechanism of PBZ's hepatorenal toxicity. At first, metabolomics analysis was done to investigate the metabolites and the related metabolic pathways associated with PBZ. Secondly, the network pharmacology approach was used in further exploration of the toxic targets. Additionally, molecular docking was carried out to investigate the interactions between PBZ and potential targets. The results indicated that PBZ showed obvious toxicity towards the liver and kidney of rats. The metabolomics analysis showed that PBZ mainly affected 4 metabolic pathways, including tryptophan metabolism, arachidonic acid metabolism, linoleic acid metabolism, and purine metabolism. Network pharmacology and molecular docking revealed that CYP1A2, CYP2A6, CYP2E1, MAOA, PLA2G2A, PTGS1, and XDH were critical targets for PBZ hepatorenal toxicity. This preliminary study revealed PBZ's hepatorenal toxicity and provided a theoretical basis for the rational and safe use of PBZ. Furthermore, it provided possible intervention targets for further research on how to avoid or reduce the damage caused by pesticides to the human body.
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Affiliation(s)
- Kexin Yue
- School of Pharmaceutical Sciences, Jilin University, Changchun 130021, China
| | - Zhiqiang Liu
- National Center of Mass Spectrometry in Changchun, Key Laboratory of Traditional Chinese Medicine Chemistry and Mass Spectrometry Jilin Province, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China
| | - Zifeng Pi
- National Center of Mass Spectrometry in Changchun, Key Laboratory of Traditional Chinese Medicine Chemistry and Mass Spectrometry Jilin Province, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China.,College of Pharmacy, Changchun University of Chinese Medicine, Changchun, Jilin 130117, China
| | - Hanlin Li
- School of Pharmaceutical Sciences, Jilin University, Changchun 130021, China
| | - Yingping Wang
- State Local Joint Engineering Research Center of Ginseng Breeding and Application, Jilin Agricultural University, Changchun 130118, China
| | - Fengrui Song
- National Center of Mass Spectrometry in Changchun, Key Laboratory of Traditional Chinese Medicine Chemistry and Mass Spectrometry Jilin Province, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China
| | - Zhongying Liu
- School of Pharmaceutical Sciences, Jilin University, Changchun 130021, China
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26
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Identificación del fenotipo ahorrador para la personalización del manejo del sobrepeso y la obesidad. REVISTA MÉDICA CLÍNICA LAS CONDES 2022. [DOI: 10.1016/j.rmclc.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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27
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Sex differences in white adipose tissue expansion: emerging molecular mechanisms. Clin Sci (Lond) 2021; 135:2691-2708. [PMID: 34908104 DOI: 10.1042/cs20210086] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/15/2021] [Accepted: 11/29/2021] [Indexed: 12/15/2022]
Abstract
The escalating prevalence of individuals becoming overweight and obese is a rapidly rising global health problem, placing an enormous burden on health and economic systems worldwide. Whilst obesity has well described lifestyle drivers, there is also a significant and poorly understood component that is regulated by genetics. Furthermore, there is clear evidence for sexual dimorphism in obesity, where overall risk, degree, subtype and potential complications arising from obesity all differ between males and females. The molecular mechanisms that dictate these sex differences remain mostly uncharacterised. Many studies have demonstrated that this dimorphism is unable to be solely explained by changes in hormones and their nuclear receptors alone, and instead manifests from coordinated and highly regulated gene networks, both during development and throughout life. As we acquire more knowledge in this area from approaches such as large-scale genomic association studies, the more we appreciate the true complexity and heterogeneity of obesity. Nevertheless, over the past two decades, researchers have made enormous progress in this field, and some consistent and robust mechanisms continue to be established. In this review, we will discuss some of the proposed mechanisms underlying sexual dimorphism in obesity, and discuss some of the key regulators that influence this phenomenon.
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28
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Flowers E, Allen IE, Kanaya AM, Aouizerat BE. Circulating microRNAs are associated with variability in fasting blood glucose over 12-months and target pathways related to type 2 diabetes: A pilot study. Diab Vasc Dis Res 2021; 18:14791641211055837. [PMID: 34846185 PMCID: PMC8761879 DOI: 10.1177/14791641211055837] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
INTRODUCTION MicroRNAs (miRs) may be important regulators of risk for type 2 diabetes (T2D). Circulating miRs may provide information about which individuals are at risk for T2D. The purpose of this study was to assess longitudinal associations between circulating miR expression and variability in fasting blood glucose (FBG) and to identify miR-targeted genes and biological pathways. METHODS Variability in FBG was estimated using standard deviation from participants (n = 20) in a previously completed yoga trial. Expression of 402 miRs was measured using hydrogel particle lithography. MirTarBase was used to identify mRNAs, and miRPathDB was used to identify pathways targeted by differentially expressed miRs. RESULTS Six circulating miRs (miR-192, miR-197, miR-206, miR-424, miR-486, and miR-93) were associated with variability in FBG and targeted 143 genes and 23 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Six mRNAs (AKT1, CCND1, ESR1, FASN, SMAD7, and VEGFA) were targeted by at least two miRs and four of those were located in miR-targeted KEGG pathways. CONCLUSIONS Circulating miRs are associated with variability in FBG in individuals at risk for T2D. Further studies are needed to determine whether miRs may be prodromal biomarkers that can identify which individuals are at greatest risk to progress to T2D and which biological pathways underlie this risk.
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Affiliation(s)
- Elena Flowers
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, CA, USA
- Elena Flowers, San Francisco Department of Physiological Nursing, University of California, 2 Koret Way, #605L, San Francisco, CA 94143-0610, USA.
| | - Isabel E Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Alka M Kanaya
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
| | - Bradley E Aouizerat
- Department of Oral and Maxillofacial Surgery, New York University, New York, NY, USA
- Bluestone Center for Clinical Research, New York University, New York, NY, USA
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Primeaux SD, Simon L, Ferguson TF, Levitt DE, Brashear MM, Yeh A, Molina PE. Alcohol use and dysglycemia among people living with human immunodeficiency virus (HIV) in the Alcohol & Metabolic Comorbidities in PLWH: Evidence Driven Interventions (ALIVE-Ex) study. Alcohol Clin Exp Res 2021; 45:1735-1746. [PMID: 34342022 PMCID: PMC8547613 DOI: 10.1111/acer.14667] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/29/2021] [Accepted: 07/01/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND At-risk alcohol use is a common and costly form of substance misuse that is highly prevalent among people living with HIV (PLWH). The goal of the current analysis was to test the hypothesis that PLWH with at-risk alcohol use are more likely to meet the clinical criteria for prediabetes/diabetes than PLWH with low-risk alcohol use. METHODS A cross-sectional analysis was performed on measures of alcohol and glycemic control in adult PLWH (n = 105) enrolled in a prospective, interventional study (the ALIVE-Ex Study (NCT03299205)) that investigated the effects of aerobic exercise on metabolic dysregulation in PLWH with at-risk alcohol use. The Alcohol Use Disorders Identification Test (AUDIT), Timeline Followback, and phosphatidylethanol (PEth) level were used to measure alcohol use. Participants were stratified into low-risk (AUDIT score < 5) and at-risk alcohol use (AUDIT score ≥ 5). All participants underwent an oral glucose tolerance test and measures of glycemic control- the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and Matsuda Index - were correlated with alcohol measures and compared by AUDIT score group using mixed-effects linear and logistic regression models, adjusting for age, sex, race, body mass index (BMI), and viral load. RESULTS In response to the glucose challenge, participants with at-risk alcohol use (n = 46) had higher glucose levels and were five times more likely to meet criteria for prediabetes/diabetes (OR: 5.3 (1.8, 15.9)) than participants with an AUDIT score < 5. Two-hour glucose values were positively associated with AUDIT score and PEth level and a higher percentage of PLWH with at-risk alcohol use had glucose values ≥140 mg/dl than those with low-risk alcohol use (34.8% vs. 10.2%, respectively). CONCLUSION In this cohort of PLWH, at-risk alcohol use increased the likelihood of meeting the clinical criteria for prediabetes/diabetes (2-h glucose level ≥140 mg/dl). Established determinants of metabolic dysfunction (e.g., BMI, waist-hip ratio) were not associated with greater alcohol use and dysglycemia, suggesting that other mechanisms may contribute to the impaired glycemic control observed in this cohort.
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Affiliation(s)
- Stefany D. Primeaux
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
- Joint Diabetes, Endocrinology & Metabolism Program, Pennington Biomedical Research Center, Baton Rouge, LA 70808
| | - Liz Simon
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
- Comprehensive Alcohol-HIV/AIDS Research Center, Louisiana State University Health Sciences Center, LA 70112
| | - Tekeda F. Ferguson
- Comprehensive Alcohol-HIV/AIDS Research Center, Louisiana State University Health Sciences Center, LA 70112
- Department of Epidemiology, Louisiana State University Health Sciences Center, New Orleans, 70112
| | - Danielle E. Levitt
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
- Comprehensive Alcohol-HIV/AIDS Research Center, Louisiana State University Health Sciences Center, LA 70112
| | - Meghan M. Brashear
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
- Comprehensive Alcohol-HIV/AIDS Research Center, Louisiana State University Health Sciences Center, LA 70112
| | - Alice Yeh
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
| | - Patricia E. Molina
- Department of Physiology, Louisiana State University Health Sciences Center, New Orleans, LA 70112
- Comprehensive Alcohol-HIV/AIDS Research Center, Louisiana State University Health Sciences Center, LA 70112
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Flowers E, Allen IE, Kanaya AM, Aouizerat BE. Circulating MicroRNAs predict glycemic improvement and response to a behavioral intervention. Biomark Res 2021; 9:65. [PMID: 34425916 PMCID: PMC8383422 DOI: 10.1186/s40364-021-00317-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/27/2021] [Indexed: 01/16/2023] Open
Abstract
Background MicroRNAs may be important regulators of risk for type 2 diabetes. The purpose of this longitudinal observational study was to assess whether circulating microRNAs predicted improvements in fasting blood glucose, a major risk factor for type 2 diabetes, over 12 months. Methods The study included participants (n = 82) from a previously completed trial that tested the effect of restorative yoga on individuals with prediabetes. Circulating microRNAs were measured using a flow cytometry miRNA assay. Linear models were used to determine the optimal sets of microRNA predictors overall and by intervention group. Results Subsets of microRNAs were significant predictors of final fasting blood glucose after 12-months (R2 = 0.754, p < 0.001) and changes in fasting blood glucose over 12-months (R2 = 0.731, p < 0.001). Three microRNAs (let-7c, miR-363, miR-374b) were significant for the control group only, however there was no significant interaction by intervention group. Conclusions Circulating microRNAs are significant predictors of fasting blood glucose in individuals with prediabetes. Among the identified microRNAs, several have previously been associated with risk for type 2 diabetes. This is one of the first studies to use a longitudinal design to assess whether microRNAs predict changes in fasting blood glucose over time. Further exploration of the function of the microRNAs included in these models may provide new insights about the complex etiology of type 2 diabetes and responses to behavioral risk reduction interventions. Trial registration This study was a secondary analysis of a previously completed clinical trial that is registered at clinicaltrials.gov (NCT01024816) on December 3, 2009. Supplementary Information The online version contains supplementary material available at 10.1186/s40364-021-00317-5.
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Affiliation(s)
- Elena Flowers
- Department of Physiological Nursing, University of California, San Francisco, 2 Koret Way, #605L, CA, 94143-0610, San Francisco, USA. .,Institute for Human Genetics, University of California, San Francisco, 2 Koret Way, #605L, CA , 94143-0610, San Francisco, USA.
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, USA
| | - Alka M Kanaya
- Department of Epidemiology and Biostatistics, University of California, San Francisco, USA.,Department of Medicine, University of California, San Francisco, USA
| | - Bradley E Aouizerat
- Bluestone Center for Clinical Research, New York University, New York, USA.,Department of Oral and Maxillofacial Surgery, New York University, New York, USA
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Qu J, Qu HQ, Bradfield JP, Glessner JT, Chang X, Tian L, March M, Connolly JJ, Roizen JD, Sleiman PMA, Hakonarson H. Insights into non-autoimmune type 1 diabetes with 13 novel loci in low polygenic risk score patients. Sci Rep 2021; 11:16013. [PMID: 34362956 PMCID: PMC8346538 DOI: 10.1038/s41598-021-94994-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/20/2021] [Indexed: 01/21/2023] Open
Abstract
With polygenic risk score (PRS) for autoimmune type 1 diabetes (T1D), this study identified T1D cases with low T1D PRS and searched for susceptibility loci in these cases. Our hypothesis is that genetic effects (likely mediated by relatively rare genetic variants) of non-mainstream (or non-autoimmune) T1D might have been diluted in the previous studies on T1D cases in general. Two cohorts for the PRS modeling and testing respectively were included. The first cohort consisted of 3302 T1D cases and 6181 controls, and the independent second cohort consisted of 3297 T1D cases and 6169 controls. Cases with low T1D PRS were identified using PRSice-2 and compared to controls with low T1D PRS by genome-wide association (GWA) test. Thirteen novel genetic loci with high imputation quality (Quality Score r2 > 0.91) were identified of SNPs/SNVs associated with low PRS T1D at genome-wide significance (P ≤ 5.0 × E-08), in addition to 4 established T1D loci, 3 reported loci by our previous study, as well as 9 potential novel loci represented by rare SNVs, but with relatively low imputation quality (Quality Score r2 < 0.90). For the 13 novel loci, 9 regions have been reported of association with obesity related traits by previous GWA studies. Three loci encoding long intergenic non-protein coding RNAs (lncRNA), and 2 loci involved in N-linked glycosylation are also highlighted in this study.
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Affiliation(s)
- Jingchun Qu
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - Hui-Qi Qu
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | | | - Joseph T. Glessner
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - Xiao Chang
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - Lifeng Tian
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - Michael March
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - John J. Connolly
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA
| | - Jeffrey D. Roizen
- grid.25879.310000 0004 1936 8972Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Patrick M. A. Sleiman
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA ,grid.25879.310000 0004 1936 8972Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA ,grid.239552.a0000 0001 0680 8770Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
| | - Hakon Hakonarson
- grid.239552.a0000 0001 0680 8770The Center for Applied Genomics, Children’s Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA 19104 USA ,grid.25879.310000 0004 1936 8972Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA ,grid.239552.a0000 0001 0680 8770Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA ,grid.239552.a0000 0001 0680 8770Division of Pulmonary Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104 USA
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Anwar MY, Raffield LM, Lange LA, Correa A, Taylor KC. Genetic underpinnings of regional adiposity distribution in African Americans: Assessments from the Jackson Heart Study. PLoS One 2021; 16:e0255609. [PMID: 34347846 PMCID: PMC8336790 DOI: 10.1371/journal.pone.0255609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 07/19/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND African ancestry individuals with comparable overall anthropometric measures to Europeans have lower abdominal adiposity. To explore the genetic underpinning of different adiposity patterns, we investigated whether genetic risk scores for well-studied adiposity phenotypes like body mass index (BMI) and waist circumference (WC) also predict other, less commonly measured adiposity measures in 2420 African American individuals from the Jackson Heart Study. METHODS Polygenic risk scores (PRS) were calculated using GWAS-significant variants extracted from published studies mostly representing European ancestry populations for BMI, waist-hip ratio (WHR) adjusted for BMI (WHRBMIadj), waist circumference adjusted for BMI (WCBMIadj), and body fat percentage (BF%). Associations between each PRS and adiposity measures including BF%, subcutaneous adiposity tissue (SAT), visceral adiposity tissue (VAT) and VAT:SAT ratio (VSR) were examined using multivariable linear regression, with or without BMI adjustment. RESULTS In non-BMI adjusted models, all phenotype-PRS were found to be positive predictors of BF%, SAT and VAT. WHR-PRS was a positive predictor of VSR, but BF% and BMI-PRS were negative predictors of VSR. After adjusting for BMI, WHR-PRS remained a positive predictor of BF%, VAT and VSR but not SAT. WC-PRS was a positive predictor of SAT and VAT; BF%-PRS was a positive predictor of BF% and SAT only. CONCLUSION These analyses suggest that genetically driven increases in BF% strongly associate with subcutaneous rather than visceral adiposity and BF% is strongly associated with BMI but not central adiposity-associated genetic variants. How common genetic variants may contribute to observed differences in adiposity patterns between African and European ancestry individuals requires further study.
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Affiliation(s)
- Mohammad Y. Anwar
- School of Public Health & Information Sciences, The University of Louisville, Louisville, KY, United States of America
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, United States of America
| | - Leslie A. Lange
- Division of Biomedical Informatics and Personalized Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Adolfo Correa
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Kira C. Taylor
- School of Public Health & Information Sciences, The University of Louisville, Louisville, KY, United States of America
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Pan DZ, Miao Z, Comenho C, Rajkumar S, Koka A, Lee SHT, Alvarez M, Kaminska D, Ko A, Sinsheimer JS, Mohlke KL, Mancuso N, Muñoz-Hernandez LL, Herrera-Hernandez M, Tusié-Luna MT, Aguilar-Salinas C, Pietiläinen KH, Pihlajamäki J, Laakso M, Garske KM, Pajukanta P. Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome Med 2021; 13:123. [PMID: 34340684 PMCID: PMC8327600 DOI: 10.1186/s13073-021-00939-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 07/14/2021] [Indexed: 12/14/2022] Open
Abstract
Background Obesity predisposes individuals to multiple cardiometabolic disorders, including type 2 diabetes (T2D). As body mass index (BMI) cannot reliably differentiate fat from lean mass, the metabolically detrimental abdominal obesity has been estimated using waist-hip ratio (WHR). Waist-hip ratio adjusted for body mass index (WHRadjBMI) in turn is a well-established sex-specific marker for abdominal fat and adiposity, and a predictor of adverse metabolic outcomes, such as T2D. However, the underlying genes and regulatory mechanisms orchestrating the sex differences in obesity and body fat distribution in humans are not well understood. Methods We searched for genetic master regulators of WHRadjBMI by employing integrative genomics approaches on human subcutaneous adipose RNA sequencing (RNA-seq) data (n ~ 1400) and WHRadjBMI GWAS data (n ~ 700,000) from the WHRadjBMI GWAS cohorts and the UK Biobank (UKB), using co-expression network, transcriptome-wide association study (TWAS), and polygenic risk score (PRS) approaches. Finally, we functionally verified our genomic results using gene knockdown experiments in a human primary cell type that is critical for adipose tissue function. Results Here, we identified an adipose gene co-expression network that contains 35 obesity GWAS genes and explains a significant amount of polygenic risk for abdominal obesity and T2D in the UKB (n = 392,551) in a sex-dependent way. We showed that this network is preserved in the adipose tissue data from the Finnish Kuopio Obesity Study and Mexican Obesity Study. The network is controlled by a novel adipose master transcription factor (TF), TBX15, a WHRadjBMI GWAS gene that regulates the network in trans. Knockdown of TBX15 in human primary preadipocytes resulted in changes in expression of 130 network genes, including the key adipose TFs, PPARG and KLF15, which were significantly impacted (FDR < 0.05), thus functionally verifying the trans regulatory effect of TBX15 on the WHRadjBMI co-expression network. Conclusions Our study discovers a novel key function for the TBX15 TF in trans regulating an adipose co-expression network of 347 adipose, mitochondrial, and metabolically important genes, including PPARG, KLF15, PPARA, ADIPOQ, and 35 obesity GWAS genes. Thus, based on our converging genomic, transcriptional, and functional evidence, we interpret the role of TBX15 to be a main transcriptional regulator in the adipose tissue and discover its importance in human abdominal obesity. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00939-2.
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Affiliation(s)
- David Z Pan
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Zong Miao
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Caroline Comenho
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Sandhya Rajkumar
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Computational and Systems Biology Interdepartmental Program, UCLA, Los Angeles, USA
| | - Amogha Koka
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Seung Hyuk T Lee
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Dorota Kaminska
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Arthur Ko
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Janet S Sinsheimer
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Linda Liliana Muñoz-Hernandez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Morones Prieto 3000, Monterrey, N.L., México, 64710.,Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Miguel Herrera-Hernandez
- Departamento de Cirugía, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico City, Mexico
| | - Maria Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/ Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos Aguilar-Salinas
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Jussi Pihlajamäki
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristina M Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA. .,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA. .,Institute for Precision Health at UCLA, Los Angeles, USA.
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Meta-analysis of genome-wide association studies and gene networks analysis for milk production traits in Holstein cows. Livest Sci 2021. [DOI: 10.1016/j.livsci.2021.104605] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Sun C, Kovacs P, Guiu-Jurado E. Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries. Genes (Basel) 2021; 12:genes12060841. [PMID: 34072523 PMCID: PMC8228180 DOI: 10.3390/genes12060841] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 05/26/2021] [Accepted: 05/27/2021] [Indexed: 12/16/2022] Open
Abstract
Preferential fat accumulation in visceral vs. subcutaneous depots makes obese individuals more prone to metabolic complications. Body fat distribution (FD) is regulated by genetics. FD patterns vary across ethnic groups independent of obesity. Asians have more and Africans have less visceral fat compared with Europeans. Consequently, Asians tend to be more susceptible to type 2 diabetes even with lower BMIs when compared with Europeans. To date, genome-wide association studies (GWAS) have identified more than 460 loci related to FD traits. However, the majority of these data were generated in European populations. In this review, we aimed to summarize recent advances in FD genetics with a focus on comparisons between European and non-European populations (Asians and Africans). We therefore not only compared FD-related susceptibility loci identified in three ethnicities but also discussed whether known genetic variants might explain the FD pattern heterogeneity across different ancestries. Moreover, we describe several novel candidate genes potentially regulating FD, including NID2, HECTD4 and GNAS, identified in studies with Asian populations. It is of note that in agreement with current knowledge, most of the proposed FD candidate genes found in Asians belong to the group of developmental genes.
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Affiliation(s)
- Chang Sun
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Esther Guiu-Jurado
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Deutsches Zentrum für Diabetesforschung, 85764 Neuherberg, Germany
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SAINI SIMMI, WALIA GAGANDEEPKAUR, SACHDEVA MOHINDERPAL, GUPTA VIPIN. Genomics of body fat distribution. J Genet 2021. [DOI: 10.1007/s12041-021-01281-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Porro S, Genchi VA, Cignarelli A, Natalicchio A, Laviola L, Giorgino F, Perrini S. Dysmetabolic adipose tissue in obesity: morphological and functional characteristics of adipose stem cells and mature adipocytes in healthy and unhealthy obese subjects. J Endocrinol Invest 2021; 44:921-941. [PMID: 33145726 DOI: 10.1007/s40618-020-01446-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 10/07/2020] [Indexed: 12/11/2022]
Abstract
The way by which subcutaneous adipose tissue (SAT) expands and undergoes remodeling by storing excess lipids through expansion of adipocytes (hypertrophy) or recruitment of new precursor cells (hyperplasia) impacts the risk of developing cardiometabolic and respiratory diseases. In unhealthy obese subjects, insulin resistance, type 2 diabetes, hypertension, and obstructive sleep apnoea are typically associated with pathologic SAT remodeling characterized by adipocyte hypertrophy, as well as chronic inflammation, hypoxia, increased visceral adipose tissue (VAT), and fatty liver. In contrast, metabolically healthy obese individuals are generally associated with SAT development characterized by the presence of smaller and numerous mature adipocytes, and a lower degree of VAT inflammation and ectopic fat accumulation. The remodeling of SAT and VAT is under genetic regulation and influenced by inherent depot-specific differences of adipose tissue-derived stem cells (ASCs). ASCs have multiple functions such as cell renewal, adipogenic capacity, and angiogenic properties, and secrete a variety of bioactive molecules involved in vascular and extracellular matrix remodeling. Understanding the mechanisms regulating the proliferative and adipogenic capacity of ASCs from SAT and VAT in response to excess calorie intake has become a focus of interest over recent decades. Here, we summarize current knowledge about the biological mechanisms able to foster or impair the recruitment and adipogenic differentiation of ASCs during SAT and VAT development, which regulate body fat distribution and favorable or unfavorable metabolic responses.
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Affiliation(s)
- S Porro
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
| | - V A Genchi
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
| | - A Cignarelli
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
| | - A Natalicchio
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
| | - L Laviola
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
| | - F Giorgino
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy.
| | - S Perrini
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, 70124, Bari, Italy
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Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring) 2021; 29:802-820. [PMID: 33899337 DOI: 10.1002/oby.23116] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/14/2022]
Abstract
There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.
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Affiliation(s)
- Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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Wardowska A. m6A RNA Methylation in Systemic Autoimmune Diseases-A New Target for Epigenetic-Based Therapy? Pharmaceuticals (Basel) 2021; 14:ph14030218. [PMID: 33807762 PMCID: PMC8001529 DOI: 10.3390/ph14030218] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 02/26/2021] [Accepted: 03/03/2021] [Indexed: 12/17/2022] Open
Abstract
The general background of autoimmune diseases is a combination of genetic, epigenetic and environmental factors, that lead to defective immune reactions. This erroneous immune cell activation results in an excessive production of autoantibodies and prolonged inflammation. During recent years epigenetic mechanisms have been extensively studied as potential culprits of autoreactivity. Alike DNA and proteins, also RNA molecules are subjected to an extensive repertoire of chemical modifications. N6-methyladenosine is the most prevalent form of internal mRNA modification in eukaryotic cells and attracts increasing attention due to its contribution to human health and disease. Even though m6A is confirmed as an essential player in immune response, little is known about its role in autoimmunity. Only few data have been published up to date in the field of RNA methylome. Moreover, only selected autoimmune diseases have been studied in respect of m6A role in their pathogenesis. In this review, I attempt to present all available research data regarding m6A alterations in autoimmune disorders and appraise its role as a potential target for epigenetic-based therapies.
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Affiliation(s)
- Anna Wardowska
- Department of Embryology, Medical University of Gdansk, 80-210 Gdansk, Poland
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Mathkar PP, Chen X, Sulovari A, Li D. Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes. Viruses 2021; 13:v13020245. [PMID: 33557409 PMCID: PMC7915589 DOI: 10.3390/v13020245] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/31/2021] [Accepted: 02/02/2021] [Indexed: 12/19/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Almost half of HCC cases are associated with hepatitis B virus (HBV) infections, which often lead to HBV sequence integrations in the human genome. Accurate identification of HBV integration sites at a single nucleotide resolution is critical for developing a better understanding of the cancer genome landscape and of the disease itself. Here, we performed further analyses and characterization of HBV integrations identified by our recently reported VIcaller platform in recurrent or known HCC genes (such as TERT, MLL4, and CCNE1) as well as non-recurrent cancer-related genes (such as CSMD2, NKD2, and RHOU). Our pathway enrichment analysis revealed multiple pathways involving the alcohol dehydrogenase 4 gene, such as the metabolism pathways of retinol, tyrosine, and fatty acid. Further analysis of the HBV integration sites revealed distinct patterns involving the integration upper breakpoints, integrated genome lengths, and integration allele fractions between tumor and normal tissues. Our analysis also implies that the VIcaller method has diagnostic potential through discovering novel clonal integrations in cancer-related genes. In conclusion, although VIcaller is a hypothesis free virome-wide approach, it can still be applied to accurately identify genome-wide integration events of a specific candidate virus and their integration allele fractions.
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Affiliation(s)
- Pranav P. Mathkar
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT 05405, USA; (P.P.M.); (A.S.)
| | - Xun Chen
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT 05405, USA; (P.P.M.); (A.S.)
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto 606-8501, Japan
- Correspondence: (X.C.); (D.L.)
| | - Arvis Sulovari
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT 05405, USA; (P.P.M.); (A.S.)
- Cajal Neuroscience Inc., Seattle, WA 98102, USA
| | - Dawei Li
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT 05405, USA; (P.P.M.); (A.S.)
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL 33431, USA
- Correspondence: (X.C.); (D.L.)
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Liu Y, Zhang X, Lee J, Smelser D, Cade B, Chen H, Zhou H, Kirchner HL, Lin X, Mukherjee S, Hillman D, Liu CT, Redline S, Sofer T. Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity. Int J Obes (Lond) 2021; 45:1532-1541. [PMID: 33907307 PMCID: PMC8236408 DOI: 10.1038/s41366-021-00817-2] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 03/06/2021] [Accepted: 04/09/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND/OBJECTIVES Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference. METHODS We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis. RESULTS We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10-9) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10-7; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins. CONCLUSIONS Our study suggests that neck circumference may have unique genetic basis independent of BMI.
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Affiliation(s)
- Yaowu Liu
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Xiaoyu Zhang
- grid.189504.10000 0004 1936 7558Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Jiwon Lee
- grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA
| | - Diane Smelser
- grid.415341.60000 0004 0433 4040Department of Molecular and Functional Genomics, Geisinger Clinic, Danville, PA USA
| | - Brian Cade
- grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Medicine, Harvard Medical School, Boston, MA USA
| | - Han Chen
- grid.267308.80000 0000 9206 2401Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX USA ,grid.267308.80000 0000 9206 2401Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX USA
| | - Hufeng Zhou
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - H. Lester Kirchner
- grid.415341.60000 0004 0433 4040Department of Population Health Sciences, Geisinger Clinic, Danville, PA USA
| | - Xihong Lin
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Statistics, Harvard University, Cambridge, MA USA
| | - Sutapa Mukherjee
- Sleep Health Service, Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, SA Australia ,grid.1014.40000 0004 0367 2697Adelaide Institute for Sleep Health, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA Australia
| | - David Hillman
- grid.1012.20000 0004 1936 7910School of Human Sciences, The University of Western Australia, Perth, WA Australia
| | - Ching-Ti Liu
- grid.189504.10000 0004 1936 7558Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Susan Redline
- grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Medicine, Harvard Medical School, Boston, MA USA
| | - Tamar Sofer
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.62560.370000 0004 0378 8294Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Medicine, Harvard Medical School, Boston, MA USA
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Ceballos FC, Hazelhurst S, Clark DW, Agongo G, Asiki G, Boua PR, Xavier Gómez-Olivé F, Mashinya F, Norris S, Wilson JF, Ramsay M. Autozygosity influences cardiometabolic disease-associated traits in the AWI-Gen sub-Saharan African study. Nat Commun 2020; 11:5754. [PMID: 33188201 PMCID: PMC7666169 DOI: 10.1038/s41467-020-19595-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 10/12/2020] [Indexed: 11/10/2022] Open
Abstract
The analysis of the effects of autozygosity, measured as the change of the mean value of a trait among offspring of genetic relatives, reveals the existence of directional dominance or overdominance. In this study we detect evidence of the effect of autozygosity in 4 out of 13 cardiometabolic disease-associated traits using data from more than 10,000 sub-Saharan African individuals recruited from Ghana, Burkina Faso, Kenya and South Africa. The effect of autozygosity on these phenotypes is found to be sex-related, with inbreeding having a significant decreasing effect in men but a significant increasing effect in women for several traits (body mass index, subcutaneous adipose tissue, low-density lipoproteins and total cholesterol levels). Overall, the effect of inbreeding depression is more intense in men. Differential effects of inbreeding depression are also observed between study sites with different night-light intensity used as proxy for urban development. These results suggest a directional dominant genetic component mediated by environmental interactions and sex-specific differences in genetic architecture for these traits in the Africa Wits-INDEPTH partnership for Genomic Studies (AWI-Gen) cohort.
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Affiliation(s)
- Francisco C Ceballos
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - David W Clark
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Godfred Agongo
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Navrongo Health Research Centre, Navrongo, Ghana
| | - Gershim Asiki
- African Population and Health Research Center, Nairobi, Kenya
| | - Palwende R Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, Nanoro, Burkina Faso
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Felistas Mashinya
- Department of Pathology and Medical Science, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Shane Norris
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Faculty of Health Sciences University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Johannesburg, South Africa.
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The role of m 6A modification in physiology and disease. Cell Death Dis 2020; 11:960. [PMID: 33162550 PMCID: PMC7649148 DOI: 10.1038/s41419-020-03143-z] [Citation(s) in RCA: 111] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 10/08/2020] [Accepted: 10/09/2020] [Indexed: 12/13/2022]
Abstract
Similar to DNA epigenetic modifications, multiple reversible chemical modifications on RNAs have been uncovered in a new layer of epigenetic modification. N6-methyladenosine (m6A), a modification that occurs in ~30% transcripts, is dynamically regulated by writer complex (methylase) and eraser (RNA demethylase) proteins, and is recognized by reader (m6A-binding) proteins. The effects of m6A modification are reflected in the functional modulation of mRNA splicing, export, localization, translation, and stability by regulating RNA structure and interactions between RNA and RNA-binding proteins. This modulation is involved in a variety of physiological behaviors, including neurodevelopment, immunoregulation, and cellular differentiation. The disruption of m6A modulations impairs gene expression and cellular function and ultimately leads to diseases such as cancer, psychiatric disorders, and metabolic disease. This review focuses on the mechanisms and functions of m6A modification in a variety of physiological behaviors and diseases.
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Investigation of gene-gene interactions in cardiac traits and serum fatty acid levels in the LURIC Health Study. PLoS One 2020; 15:e0238304. [PMID: 32915819 PMCID: PMC7485803 DOI: 10.1371/journal.pone.0238304] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 08/13/2020] [Indexed: 01/25/2023] Open
Abstract
Epistasis analysis elucidates the effects of gene-gene interactions (G×G) between multiple loci for complex traits. However, the large computational demands and the high multiple testing burden impede their discoveries. Here, we illustrate the utilization of two methods, main effect filtering based on individual GWAS results and biological knowledge-based modeling through Biofilter software, to reduce the number of interactions tested among single nucleotide polymorphisms (SNPs) for 15 cardiac-related traits and 14 fatty acids. We performed interaction analyses using the two filtering methods, adjusting for age, sex, body mass index (BMI), waist-hip ratio, and the first three principal components from genetic data, among 2,824 samples from the Ludwigshafen Risk and Cardiovascular (LURIC) Health Study. Using Biofilter, one interaction nearly met Bonferroni significance: an interaction between rs7735781 in XRCC4 and rs10804247 in XRCC5 was identified for venous thrombosis with a Bonferroni-adjusted likelihood ratio test (LRT) p: 0.0627. A total of 57 interactions were identified from main effect filtering for the cardiac traits G×G (10) and fatty acids G×G (47) at Bonferroni-adjusted LRT p < 0.05. For cardiac traits, the top interaction involved SNPs rs1383819 in SNTG1 and rs1493939 (138kb from 5’ of SAMD12) with Bonferroni-adjusted LRT p: 0.0228 which was significantly associated with history of arterial hypertension. For fatty acids, the top interaction between rs4839193 in KCND3 and rs10829717 in LOC107984002 with Bonferroni-adjusted LRT p: 2.28×10−5 was associated with 9-trans 12-trans octadecanoic acid, an omega-6 trans fatty acid. The model inflation factor for the interactions under different filtering methods was evaluated from the standard median and the linear regression approach. Here, we applied filtering approaches to identify numerous genetic interactions related to cardiac-related outcomes as potential targets for therapy. The approaches described offer ways to detect epistasis in the complex traits and to improve precision medicine capability.
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Venkannagari H, Kasper JM, Misra A, Rush SA, Fan S, Lee H, Sun H, Seshadrinathan S, Machius M, Hommel JD, Rudenko G. Highly Conserved Molecular Features in IgLONs Contrast Their Distinct Structural and Biological Outcomes. J Mol Biol 2020; 432:5287-5303. [PMID: 32710982 DOI: 10.1016/j.jmb.2020.07.014] [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: 02/26/2020] [Revised: 07/17/2020] [Accepted: 07/20/2020] [Indexed: 11/16/2022]
Abstract
Neuronal growth regulator 1 (NEGR1) and neurotrimin (NTM) are abundant cell-surface proteins found in the brain and form part of the IgLON (Immunoglobulin LSAMP, OBCAM, Neurotrimin) family. In humans, NEGR1 is implicated in obesity and mental disorders, while NTM is linked to intelligence and cognitive function. IgLONs dimerize homophilically and heterophilically, and they are thought to shape synaptic connections and neural circuits by acting in trans (spanning cellular junctions) and/or in cis (at the same side of a junction). Here, we reveal homodimeric structures of NEGR1 and NTM. They assemble into V-shaped complexes via their Ig1 domains, and disruption of the Ig1-Ig1 interface abolishes dimerization in solution. A hydrophobic ridge from one Ig1 domain inserts into a hydrophobic pocket from the opposing Ig1 domain producing an interaction interface that is highly conserved among IgLONs but remarkably plastic structurally. Given the high degree of sequence conservation at the interaction interface, we tested whether different IgLONs could elicit the same biological effect in vivo. In a small-scale study administering different soluble IgLONs directly into the brain and monitoring feeding, only NEGR1 altered food intake significantly. Taking NEGR1 as a prototype, our studies thus indicate that while IgLONs share a conserved mode of interaction and are able to bind each other as homomers and heteromers, they are structurally plastic and can exert unique biological action.
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Affiliation(s)
- Harikanth Venkannagari
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - James M Kasper
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Center for Addiction Research, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Anurag Misra
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Scott A Rush
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Shanghua Fan
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Hubert Lee
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Hong Sun
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Center for Addiction Research, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Suchithra Seshadrinathan
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Mischa Machius
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Jonathan D Hommel
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Center for Addiction Research, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Gabby Rudenko
- Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX 77555, USA; Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA; Center for Addiction Research, University of Texas Medical Branch, Galveston, TX 77555, USA.
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Association of serum uric acid with visceral, subcutaneous and hepatic fat quantified by magnetic resonance imaging. Sci Rep 2020; 10:442. [PMID: 31949261 PMCID: PMC6965096 DOI: 10.1038/s41598-020-57459-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 12/28/2019] [Indexed: 12/20/2022] Open
Abstract
Elevated serum uric acid (SUA) is associated with a variety of medical conditions, such as hypertension, diabetes and obesity. Analyses investigating uric acid and obesity were primarily conducted using anthropometric measures like BMI and waist circumference. However, different adipose tissue depots might be differentially affected in uric acid metabolism. We analyzed the relation of SUA with visceral, subcutaneous and hepatic fat as quantified by Magnetic Resonance Imaging in N = 371 individuals from a cross-sectional sample of a population-based cohort. Associations of SUA and fat depots were calculated by regressions adjusted for potential confounders. We found that SUA was correlated with all fat measures (e.g. Pearson’s r between SUA and hepatic fat: 0.50, 95%-CI: 0.42, 0.57). Associations with visceral and hepatic fat, but not with subcutaneous fat, remained evident after adjustment for anthropometric measures (e.g. visceral fat: β = 0.51 l, 95%-CI: 0.30 l, 0.72 l). In conclusion, these results show how different adipose tissue compartments are affected by SUA to varying degrees, thus emphasizing the different physiological roles of these adipose tissues in uric acid metabolism.
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47
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Kentistou KA, Wilson JF, Joshi PK, Morton NM. The genetic underpinnings of obesity. CURRENT OPINION IN PHYSIOLOGY 2019. [DOI: 10.1016/j.cophys.2019.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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48
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Lumish HS, O'Reilly M, Reilly MP. Sex Differences in Genomic Drivers of Adipose Distribution and Related Cardiometabolic Disorders: Opportunities for Precision Medicine. Arterioscler Thromb Vasc Biol 2019; 40:45-60. [PMID: 31747800 DOI: 10.1161/atvbaha.119.313154] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
This review focuses on the human genetics, epidemiology, and molecular pathophysiology of sex differences in central obesity, adipose distribution, and related cardiometabolic disorders. Distribution of fat is important for cardiometabolic health, with peripheral fat depots having a protective effect and central visceral fat depots conferring a detrimental effect on health. There are important sex differences in fat distribution that are masked when studying body mass index as a measure of obesity. From epidemiological, murine, and in vitro studies, several mechanisms have been proposed to explain the sex differences in adipose distribution, including sex hormonal effects, cell-intrinsic properties, and the microenvironment in fat depots. More recently, human genetics have revealed hundreds of loci for central obesity providing disruptive opportunities for mechanistic discoveries and clinical translation. A striking feature is that over one-third of these loci have reproducible but poorly understood sexual dimorphic associations with central obesity, most having stronger effects in women. Understanding the genetic and molecular mechanisms of adipose distribution and its sexual dimorphism in humans provides a unique opportunity to promote the use of precision medicine for early identification of at-risk individuals, and the development of novel therapeutic strategies for central obesity and related cardiometabolic disorders.
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Affiliation(s)
- Heidi S Lumish
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.)
| | - Marcella O'Reilly
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.)
| | - Muredach P Reilly
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.).,Irving Institute for Clinical and Translational Research, Columbia University, New York, NY (M.P.R.)
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Genetic analysis of hsCRP in American Indians: The Strong Heart Family Study. PLoS One 2019; 14:e0223574. [PMID: 31622379 PMCID: PMC6797125 DOI: 10.1371/journal.pone.0223574] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 09/24/2019] [Indexed: 02/07/2023] Open
Abstract
Background Increased serum levels of C-reactive protein (CRP), an important component of the innate immune response, are associated with increased risk of cardiovascular disease (CVD). Multiple single nucleotide polymorphisms (SNP) have been identified which are associated with CRP levels, and Mendelian randomization studies have shown a positive association between SNPs increasing CRP expression and risk of colon cancer (but thus far not CVD). The effects of individual genetic variants often interact with the genetic background of a population and hence we sought to resolve the genetic determinants of serum CRP in a number of American Indian populations. Methods The Strong Heart Family Study (SHFS) has serum CRP measurements from 2428 tribal members, recruited as large families from three regions of the United States. Microsatellite markers and MetaboChip defined SNP genotypes were incorporated into variance components, decomposition-based linkage and association analyses. Results CRP levels exhibited significant heritability (h2 = 0.33 ± 0.05, p<1.3 X 10−20). A locus on chromosome (chr) 6, near marker D6S281 (approximately at 169.6 Mb, GRCh38/hg38) showed suggestive linkage (LOD = 1.9) to CRP levels. No individual SNPs were found associated with CRP levels after Bonferroni adjustment for multiple testing (threshold <7.77 x 10−7), however, we found nominal associations, many of which replicate previous findings at the CRP, HNF1A and 7 other loci. In addition, we report association of 46 SNPs located at 7 novel loci on chromosomes 2, 5, 6(2 loci), 9, 10 and 17, with an average of 15.3 Kb between SNPs and all with p-values less than 7.2 X 10−4. Conclusion In agreement with evidence from other populations, these data show CRP serum levels are under considerable genetic influence; and include loci, such as near CRP and other genes, that replicate results from other ethnic groups. These findings also suggest possible novel loci on chr 6 and other chromosomes that warrant further investigation.
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Karlsson T, Rask-Andersen M, Pan G, Höglund J, Wadelius C, Ek WE, Johansson Å. Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease. Nat Med 2019; 25:1390-1395. [DOI: 10.1038/s41591-019-0563-7] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 07/29/2019] [Indexed: 12/17/2022]
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