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Trans-Ethnic Polygenic Analysis Supports Genetic Overlaps of Lumbar Disc Degeneration With Height, Body Mass Index, and Bone Mineral Density

Overview of attention for article published in Frontiers in Genetics, August 2018
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Title
Trans-Ethnic Polygenic Analysis Supports Genetic Overlaps of Lumbar Disc Degeneration With Height, Body Mass Index, and Bone Mineral Density
Published in
Frontiers in Genetics, August 2018
DOI 10.3389/fgene.2018.00267
Pubmed ID
Authors

Xueya Zhou, Ching-Lung Cheung, Tatsuki Karasugi, Jaro Karppinen, Dino Samartzis, Yi-Hsiang Hsu, Timothy Shin-Heng Mak, You-Qiang Song, Kazuhiro Chiba, Yoshiharu Kawaguchi, Yan Li, Danny Chan, Kenneth Man-Chee Cheung, Shiro Ikegawa, Kathryn Song-Eng Cheah, Pak Chung Sham

Abstract

Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, but phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 16%
Student > Bachelor 7 13%
Student > Ph. D. Student 6 11%
Student > Master 6 11%
Student > Doctoral Student 4 7%
Other 6 11%
Unknown 18 32%
Readers by discipline Count As %
Medicine and Dentistry 11 20%
Biochemistry, Genetics and Molecular Biology 6 11%
Nursing and Health Professions 6 11%
Agricultural and Biological Sciences 3 5%
Social Sciences 2 4%
Other 6 11%
Unknown 22 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 August 2018.
All research outputs
#18,645,475
of 23,098,660 outputs
Outputs from Frontiers in Genetics
#7,177
of 12,152 outputs
Outputs of similar age
#254,520
of 331,034 outputs
Outputs of similar age from Frontiers in Genetics
#133
of 159 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,152 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.