Literature DB >> 29444804

Partitioning the Pleiotropy Between Coronary Artery Disease and Body Mass Index Reveals the Importance of Low Frequency Variants and Central Nervous System-Specific Functional Elements.

Majid Nikpay1, Adam W Turner2, Ruth McPherson1.   

Abstract

BACKGROUND: The objective of this study is to investigate the extent and nature of pleiotropy between coronary artery disease (CAD) and body mass index (BMI).
METHODS: We examined the contribution of genome-wide single-nucleotide polymorphisms (minor allele frequency ≥0.01) to co-occurrence of CAD and BMI in a sample of genetically unrelated 8041 subjects (genetic resemblance ≤0.025) of European ancestry using mixed-linear-models. We further partitioned the estimated pleiotropy according to biological features to gain insight into the nature of pleiotropy between CAD and BMI.
RESULTS: We found significant (P<0.0001) positive genetic correlation between CAD and BMI (rg =0.60). The estimated pleiotropy explained 68% of phenotypic correlation, and it was not proportionally distributed across the chromosomes; notably, chromosome 10 contributed more; whereas, chromosomes 11 and 14 contributed less to pleiotropy than expected given their chromosomal length. We noted that a large proportion (63%; P=0.002) of the pleiotropy is attributed to single-nucleotide polymorphisms with low allele frequency (minor allele frequency <0.05). Of note, pleiotropy was enriched among central nervous system genes and genes of metabolic pathways. Further analyses revealed that these effects are more pronounced in the proopiomelanocortin pathway and genes involved in carbohydrate metabolism. After genome-wide association study meta-analysis, only single-nucleotide polymorphisms downstream of the MC4R gene were found concordantly associated with (P<5×10-8) BMI and CAD with lead single-nucleotide polymorphism being rs663129 (combined P=2.7×10-65). Finally, partitioning the pleiotropy according to functional elements pointed to the importance of superenhancers and notably brain-specific superenhancers.
CONCLUSIONS: Genome-wide pleiotropy substantially contributes to co-occurrence of CAD and obesity, and it is highly enriched among low frequency variants and central nervous system-specific functional elements.
© 2018 American Heart Association, Inc.

Entities:  

Keywords:  body mass index; central nervous system; coronary artery disease; gene frequency; polymorphism, single nucleotide

Mesh:

Year:  2018        PMID: 29444804     DOI: 10.1161/CIRCGEN.117.002050

Source DB:  PubMed          Journal:  Circ Genom Precis Med        ISSN: 2574-8300


  7 in total

1.  A genome-wide scan for pleiotropy between bone mineral density and nonbone phenotypes.

Authors:  Maria A Christou; Georgios Ntritsos; Georgios Markozannes; Fotis Koskeridis; Spyros N Nikas; David Karasik; Douglas P Kiel; Evangelos Evangelou; Evangelia E Ntzani
Journal:  Bone Res       Date:  2020-07-01       Impact factor: 13.567

2.  Phenome-wide screening for traits causally associated with the risk of coronary artery disease.

Authors:  Majid Nikpay; Sara Mohammadzadeh
Journal:  J Hum Genet       Date:  2020-01-07       Impact factor: 3.172

3.  RIPK1 gene variants associate with obesity in humans and can be therapeutically silenced to reduce obesity in mice.

Authors:  Denuja Karunakaran; Adam W Turner; Anne-Claire Duchez; Sebastien Soubeyrand; Adil Rasheed; David Smyth; David P Cook; Majid Nikpay; Joshua W Kandiah; Calvin Pan; Michele Geoffrion; Richard Lee; Ludovic Boytard; Hailey Wyatt; My-Anh Nguyen; Paulina Lau; Markku Laakso; Bhama Ramkhelawon; Marcus Alvarez; Kirsi H Pietiläinen; Päivi Pajukanta; Barbara C Vanderhyden; Peter Liu; Scott B Berger; Peter J Gough; John Bertin; Mary-Ellen Harper; Aldons J Lusis; Ruth McPherson; Katey J Rayner
Journal:  Nat Metab       Date:  2020-09-28

4.  A genome-wide scan for pleiotropy between bone mineral density and nonbone phenotypes.

Authors:  Maria A Christou; Georgios Ntritsos; Georgios Markozannes; Fotis Koskeridis; Spyros N Nikas; David Karasik; Douglas P Kiel; Evangelos Evangelou; Evangelia E Ntzani
Journal:  Bone Res       Date:  2020-07-01       Impact factor: 13.567

5.  PDX1 and MC4R genetic polymorphisms are associated with type 2 diabetes mellitus risk in the Chinese Han population.

Authors:  Ning Wang; Rui Tong; Jing Xu; Yanni Tian; Juan Pan; Jiaqi Cui; Huan Chen; Yanqi Peng; Sijia Fei; Shujun Yang; Lu Wang; Juanchuan Yao; Wei Cui
Journal:  BMC Med Genomics       Date:  2021-10-25       Impact factor: 3.063

6.  A unified framework identifies new links between plasma lipids and diseases from electronic medical records across large-scale cohorts.

Authors:  Yogasudha Veturi; Anastasia Lucas; Yuki Bradford; Daniel Hui; Scott Dudek; Elizabeth Theusch; Anurag Verma; Jason E Miller; Iftikhar Kullo; Hakon Hakonarson; Patrick Sleiman; Daniel Schaid; Charles M Stein; Digna R Velez Edwards; QiPing Feng; Wei-Qi Wei; Marisa W Medina; Ronald M Krauss; Thomas J Hoffmann; Neil Risch; Benjamin F Voight; Daniel J Rader; Marylyn D Ritchie
Journal:  Nat Genet       Date:  2021-06-17       Impact factor: 38.330

7.  Heterozygous Nme7 Mutation Affects Glucose Tolerance in Male Rats.

Authors:  Lucie Šedová; Jan Prochazka; Dagmar Zudová; Běla Bendlová; Josef Včelák; Radislav Sedlacek; Ondřej Šeda
Journal:  Genes (Basel)       Date:  2021-07-18       Impact factor: 4.096

  7 in total

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