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Manju SK, Anilkumar TR, Vysakh G, Leena BK, Lekshminarayan V, Kumar PG, Shenoy TK. A Case-Control Study of the Association of Leptin Gene Polymorphisms with Plasma Leptin Levels and Obesity in the Kerala Population. J Obes 2022; 2022:1040650. [PMID: 36619235 PMCID: PMC9812639 DOI: 10.1155/2022/1040650] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Over the last few years, the importance of leptin in energy metabolism has been extensively studied in both animal models and in humans. Very few results are available on the association between human leptin gene (LEP) variants and obesity traits in India. We designed this study to analyse the polymorphisms in human leptin gene and the association of sequence variants with obesity among the population in Kerala, South India. METHODS In this case-control design of 148 study participants, data were collected on socioeconomic aspects and anthropometric measurements. Plasma glucose, insulin, leptin, and lipid profile were measured. Genotyping was done by automated DNA sequencing. RESULTS The common Single Nucleotide Polymorphism (SNP) of 5'-UTR of LEP - 2548G/A was found to be present in the study population with "A" variant as dominant allele. A novel synonymous mutation Thr5Thr of exon 2 of LEP was identified in heterozygous form in one subject with morbid obesity with hyperleptinemia. A novel missense mutation Phe17Leu was observed in two subjects with obesity in heterozygous condition. A novel missense mutation Lys36Arg in exon 2 of LEP was observed in one subject with abdominal obesity and decreased serum leptin level. CONCLUSION LEP - 2548G/A at 5'-untranslated region was found to be common with the mutant "A" variant in the study population. SNPs of exons in LEP were found to be rare but associated with morbid obesity and altered levels of serum leptin in the study population in Kerala, India.
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Affiliation(s)
- Sudharmadevi K. Manju
- Department of Biochemistry, Sree Gokulam Medical College and Research Foundation, Thiruvananthapuram 695607, Kerala, India
| | - Thottathil R. Anilkumar
- Division of Molecular Reproduction, Rajiv Gandhi Centre for Biotechnology, Thycaud PO, Poojappura, Thiruvananthapuram 695014, Kerala, India
| | - G. Vysakh
- Division of Molecular Reproduction, Rajiv Gandhi Centre for Biotechnology, Thycaud PO, Poojappura, Thiruvananthapuram 695014, Kerala, India
| | - Balakumaran K. Leena
- Population Health and Research Institute, Medical College P.O., Thiruvananthapuram 695011, Kerala, India
| | | | - Pradeep G. Kumar
- Division of Molecular Reproduction, Rajiv Gandhi Centre for Biotechnology, Thycaud PO, Poojappura, Thiruvananthapuram 695014, Kerala, India
| | - Trivikrama K. Shenoy
- Department of Gastroenterology, Sree Gokulam Medical College and Research Foundation, Thiruvananthapuram 695607, Kerala, India
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Noell G, Faner R, Agustí A. From systems biology to P4 medicine: applications in respiratory medicine. Eur Respir Rev 2018; 27:27/147/170110. [PMID: 29436404 PMCID: PMC9489012 DOI: 10.1183/16000617.0110-2017] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 11/30/2017] [Indexed: 12/22/2022] Open
Abstract
Human health and disease are emergent properties of a complex, nonlinear, dynamic multilevel biological system: the human body. Systems biology is a comprehensive research strategy that has the potential to understand these emergent properties holistically. It stems from advancements in medical diagnostics, “omics” data and bioinformatic computing power. It paves the way forward towards “P4 medicine” (predictive, preventive, personalised and participatory), which seeks to better intervene preventively to preserve health or therapeutically to cure diseases. In this review, we: 1) discuss the principles of systems biology; 2) elaborate on how P4 medicine has the potential to shift healthcare from reactive medicine (treatment of illness) to predict and prevent illness, in a revolution that will be personalised in nature, probabilistic in essence and participatory driven; 3) review the current state of the art of network (systems) medicine in three prevalent respiratory diseases (chronic obstructive pulmonary disease, asthma and lung cancer); and 4) outline current challenges and future goals in the field. Systems biology and network medicine have the potential to transform medical research and practicehttp://ow.ly/r3jR30hf35x
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Affiliation(s)
- Guillaume Noell
- Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Barcelona, Spain
| | - Rosa Faner
- Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,CIBER Enfermedades Respiratorias (CIBERES), Barcelona, Spain
| | - Alvar Agustí
- Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain .,CIBER Enfermedades Respiratorias (CIBERES), Barcelona, Spain.,Respiratory Institute, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain
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Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity. Clin Sci (Lond) 2017; 130:943-86. [PMID: 27154742 DOI: 10.1042/cs20160136] [Citation(s) in RCA: 248] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 02/24/2016] [Indexed: 12/19/2022]
Abstract
In high-, middle- and low-income countries, the rising prevalence of obesity is the underlying cause of numerous health complications and increased mortality. Being a complex and heritable disorder, obesity results from the interplay between genetic susceptibility, epigenetics, metagenomics and the environment. Attempts at understanding the genetic basis of obesity have identified numerous genes associated with syndromic monogenic, non-syndromic monogenic, oligogenic and polygenic obesity. The genetics of leanness are also considered relevant as it mirrors some of obesity's aetiologies. In this report, we summarize ten genetically elucidated obesity syndromes, some of which are involved in ciliary functioning. We comprehensively review 11 monogenic obesity genes identified to date and their role in energy maintenance as part of the leptin-melanocortin pathway. With the emergence of genome-wide association studies over the last decade, 227 genetic variants involved in different biological pathways (central nervous system, food sensing and digestion, adipocyte differentiation, insulin signalling, lipid metabolism, muscle and liver biology, gut microbiota) have been associated with polygenic obesity. Advances in obligatory and facilitated epigenetic variation, and gene-environment interaction studies have partly accounted for the missing heritability of obesity and provided additional insight into its aetiology. The role of gut microbiota in obesity pathophysiology, as well as the 12 genes associated with lipodystrophies is discussed. Furthermore, in an attempt to improve future studies and merge the gap between research and clinical practice, we provide suggestions on how high-throughput '-omic' data can be integrated in order to get closer to the new age of personalized medicine.
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Langlois C, Abadi A, Peralta-Romero J, Alyass A, Suarez F, Gomez-Zamudio J, Burguete-Garcia AI, Yazdi FT, Cruz M, Meyre D. Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents. Sci Rep 2016; 6:36202. [PMID: 27782183 PMCID: PMC5080582 DOI: 10.1038/srep36202] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 10/12/2016] [Indexed: 12/15/2022] Open
Abstract
Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population.
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Affiliation(s)
- Christine Langlois
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Arkan Abadi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Jesus Peralta-Romero
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Akram Alyass
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Fernando Suarez
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Jaime Gomez-Zamudio
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Ana I. Burguete-Garcia
- Centro de investigación sobre enfermedades infecciosas. Instituto Nacional de Salud Pública. Cuernavaca, Morelos, Mexico
| | - Fereshteh T. Yazdi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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Delaney SK, Christman MF. Encouraging physician adoption of genetic testing for precision medicine. Per Med 2016; 13:201-204. [DOI: 10.2217/pme-2016-0005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Susan K Delaney
- Coriell Institute for Medical Research, 403 Haddon Avenue, Camden, NJ 08103, USA
| | - Michael F Christman
- Coriell Institute for Medical Research, 403 Haddon Avenue, Camden, NJ 08103, USA
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Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genomics 2015; 8:33. [PMID: 26112054 PMCID: PMC4482045 DOI: 10.1186/s12920-015-0108-y] [Citation(s) in RCA: 228] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 06/15/2015] [Indexed: 02/07/2023] Open
Abstract
Recent advances in high-throughput technologies have led to the emergence of systems biology as a holistic science to achieve more precise modeling of complex diseases. Many predict the emergence of personalized medicine in the near future. We are, however, moving from two-tiered health systems to a two-tiered personalized medicine. Omics facilities are restricted to affluent regions, and personalized medicine is likely to widen the growing gap in health systems between high and low-income countries. This is mirrored by an increasing lag between our ability to generate and analyze big data. Several bottlenecks slow-down the transition from conventional to personalized medicine: generation of cost-effective high-throughput data; hybrid education and multidisciplinary teams; data storage and processing; data integration and interpretation; and individual and global economic relevance. This review provides an update of important developments in the analysis of big data and forward strategies to accelerate the global transition to personalized medicine.
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Affiliation(s)
- Akram Alyass
- Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, ON, Canada.
| | - Michelle Turcotte
- Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, ON, Canada.
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, ON, Canada.
- Department of Pathology and Molecular Medicine, McMaster University, 1280 Main Street West, Hamilton, ON, Canada.
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Yazdi FT, Clee SM, Meyre D. Obesity genetics in mouse and human: back and forth, and back again. PeerJ 2015; 3:e856. [PMID: 25825681 PMCID: PMC4375971 DOI: 10.7717/peerj.856] [Citation(s) in RCA: 105] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2014] [Accepted: 03/05/2015] [Indexed: 12/19/2022] Open
Abstract
Obesity is a major public health concern. This condition results from a constant and complex interplay between predisposing genes and environmental stimuli. Current attempts to manage obesity have been moderately effective and a better understanding of the etiology of obesity is required for the development of more successful and personalized prevention and treatment options. To that effect, mouse models have been an essential tool in expanding our understanding of obesity, due to the availability of their complete genome sequence, genetically identified and defined strains, various tools for genetic manipulation and the accessibility of target tissues for obesity that are not easily attainable from humans. Our knowledge of monogenic obesity in humans greatly benefited from the mouse obesity genetics field. Genes underlying highly penetrant forms of monogenic obesity are part of the leptin-melanocortin pathway in the hypothalamus. Recently, hypothesis-generating genome-wide association studies for polygenic obesity traits in humans have led to the identification of 119 common gene variants with modest effect, most of them having an unknown function. These discoveries have led to novel animal models and have illuminated new biologic pathways. Integrated mouse-human genetic approaches have firmly established new obesity candidate genes. Innovative strategies recently developed by scientists are described in this review to accelerate the identification of causal genes and deepen our understanding of obesity etiology. An exhaustive dissection of the molecular roots of obesity may ultimately help to tackle the growing obesity epidemic worldwide.
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Affiliation(s)
- Fereshteh T. Yazdi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Susanne M. Clee
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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