Literature DB >> 30353704

Established and emerging strategies to crack the genetic code of obesity.

V Tam1, M Turcotte1, D Meyre1,2.   

Abstract

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.
© 2018 World Obesity Federation.

Entities:  

Keywords:  Candidate gene; gene identification strategies; genome-wide association study; next-generation sequencing

Mesh:

Year:  2018        PMID: 30353704     DOI: 10.1111/obr.12770

Source DB:  PubMed          Journal:  Obes Rev        ISSN: 1467-7881            Impact factor:   9.213


  8 in total

1.  Maternal BMI-Increasing Genetic Risk Score and Fetal Weights among Diverse US Ethnic Groups.

Authors:  Deepika Shrestha; Mohammad L Rahman; Stefanie N Hinkle; Tsegaselassie Workalemahu; Fasil Tekola-Ayele
Journal:  Obesity (Silver Spring)       Date:  2019-07       Impact factor: 5.002

2.  Phenome-wide screening of GWAS data reveals the complex causal architecture of obesity.

Authors:  Luis M García-Marín; Adrián I Campos; Pik-Fang Kho; Nicholas G Martin; Gabriel Cuéllar-Partida; Miguel E Rentería
Journal:  Hum Genet       Date:  2021-05-31       Impact factor: 4.132

3.  Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome.

Authors:  Karen C Clark; Anne E Kwitek
Journal:  Compr Physiol       Date:  2021-12-29       Impact factor: 8.915

Review 4.  Benefits and limitations of genome-wide association studies.

Authors:  Vivian Tam; Nikunj Patel; Michelle Turcotte; Yohan Bossé; Guillaume Paré; David Meyre
Journal:  Nat Rev Genet       Date:  2019-08       Impact factor: 53.242

Review 5.  Epigenetic contribution to obesity.

Authors:  Meriem Ouni; Annette Schürmann
Journal:  Mamm Genome       Date:  2020-04-11       Impact factor: 2.957

6.  Genome-wide association study of morbid obesity in Han Chinese.

Authors:  Kuang-Mao Chiang; Heng-Cheng Chang; Hsin-Chou Yang; Chien-Hsiun Chen; Hsin-Hung Chen; Wei-Jei Lee; Wen-Harn Pan
Journal:  BMC Genet       Date:  2019-12-18       Impact factor: 2.797

7.  Long non-coding RNAs in regulation of adipogenesis and adipose tissue function.

Authors:  Tiziana Squillaro; Gianfranco Peluso; Umberto Galderisi; Giovanni Di Bernardo
Journal:  Elife       Date:  2020-07-30       Impact factor: 8.140

8.  Association of the NEGR1 rs2815752 with obesity and related traits in Pakistani females.

Authors:  Sobia Rana; Maha Mobin
Journal:  Ups J Med Sci       Date:  2020-05-18       Impact factor: 2.384

  8 in total

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