Polygenic Models Partially Predict Muscle Size and Strength but Not Low Muscle Mass in Older Women

Khanal, Praval and Morse, Christopher I. and He, Lingxiao and Herbert, Adam J. and Onambélé-Pearson, Gladys L. and Degens, Hans and Thomis, Martine and Williams, Alun G. and Stebbings, Georgina K. (2022) Polygenic Models Partially Predict Muscle Size and Strength but Not Low Muscle Mass in Older Women. Genes, 13 (6). ISSN 2073-4425

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Abstract

BACKGROUND

Heritability explains 45-82% of muscle mass and strength variation, yet polygenic models for muscle phenotypes in older women are scarce. Therefore, the objective of the present study was to (1) assess if total genotype predisposition score (GPS) for a set of polymorphisms differed between older women with low and high muscle mass, and (2) utilise a data-driven GPS (GPS) to predict the variance in muscle size and strength-related phenotypes.

METHODS

In three-hundred 60- to 91-year-old Caucasian women (70.7 ± 5.7 years), skeletal muscle mass, biceps brachii thickness, vastus lateralis anatomical cross-sectional area (VL), hand grip strength (HGS), and elbow flexion (MVC) and knee extension (MVC) maximum voluntary contraction were measured. Participants were classified as having low muscle mass if the skeletal muscle index (SMI) < 6.76 kg/m or relative skeletal muscle mass (%SMM) < 22.1%. Genotyping was completed for 24 single-nucleotide polymorphisms (SNPs). GPS was calculated from 23 SNPs and compared between the low and high muscle mass groups. A GPS was performed to identify the association of SNPs with other skeletal muscle phenotypes.

RESULTS

There was no significant difference in GPS between low and high muscle mass groups, irrespective of classification based on SMI or %SMM. The GPS model, using 23 selected SNPs, revealed that 13 SNPs were associated with at least one skeletal muscle phenotype: rs11549465 was associated with four phenotypes and, in descending number of phenotype associations, rs4341 with three; rs7460 and rs2070802 with two; and rs17421511, rs10783485, rs1800169, rs1801131, rs1537516, rs7832552, rs1805086, rs1800012, and rs9939609 with one phenotype. The GPS with age included as a predictor variable explained 1.7% variance of biceps brachii thickness, 12.5% of VL, 19.0% of HGS, 8.2% of MVC, and 9.6% of MVC.

CONCLUSIONS

In older women, GPS did not differ between low and high muscle mass groups. However, GPS was associated with muscle size and strength phenotypes. Further advancement of polygenic models to understand skeletal muscle function during ageing might become useful in targeting interventions towards older adults most likely to lose physical independence.

Item Type: Article
Identification Number: https://doi.org/10.3390/genes13060982
Dates:
DateEvent
21 May 2022Accepted
30 May 2022Published Online
Uncontrolled Keywords: polygenic model; predisposing allele; skeletal muscle phenotypes; low and high muscle mass
Subjects: CAH02 - subjects allied to medicine > CAH02-05 - medical sciences > CAH02-05-02 - healthcare science (non-specific)
CAH02 - subjects allied to medicine > CAH02-05 - medical sciences > CAH02-05-04 - anatomy, physiology and pathology
CAH03 - biological and sport sciences > CAH03-01 - biosciences > CAH03-01-07 - genetics
CAH03 - biological and sport sciences > CAH03-02 - sport and exercise sciences > CAH03-02-01 - sport and exercise sciences
Divisions: Faculty of Health, Education and Life Sciences > Centre for Life and Sport Sciences (C-LASS)
Depositing User: Adam Herbert
Date Deposited: 07 Jul 2022 13:33
Last Modified: 07 Jul 2022 13:33
URI: http://www.open-access.bcu.ac.uk/id/eprint/13397

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