Postmenopausal Osteoporosis reference genes for qPCR expression assays

• Published in: Scientific reports Vol. 9; no. 1; pp. 16533 - 8
• Main Authors: de Lima, Camilla Albertina Dantas, de Lima, Suelen Cristina, Barbosa, Alexandre Domingues, Sandrin-Garcia, Paula, de Barros Pita, Will, de Azevêdo Silva, Jaqueline, Crovella, Sergio
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 11-11-2019; Nature Publishing Group
• Subjects: 38/39; 38/77; 38/90; 631/208; 631/208/199; Aged; Aged, 80 and over; Biomarkers; Computational Biology - methods; Female; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Genetic factors; Genetic Predisposition to Disease; Glucosephosphate dehydrogenase; Glyceraldehyde-3-phosphate dehydrogenase; Hsp90 protein; Humanities and Social Sciences; Humans; multidisciplinary; Osteoporosis; Osteoporosis, Postmenopausal - genetics; Peripheral blood mononuclear cells; Polymerase chain reaction; Post-menopause; Real-Time Polymerase Chain Reaction; Reproducibility of Results; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-52612-9

Osteoporosis (OP) is a multifactorial disease influenced by genetic factors in more than half of the cases. In spite of the efforts to clarify the relationship among genetic factors and susceptibility to develop OP, many genetic associations need to be further functionally validated. Besides, some limitations as the choice of stably expressed reference genes (RG) should be overcome to ensure the quality and reproducibility of gene expression assays. To our knowledge, a validation study for RG in OP is still missing. We compared the expression levels, using polymerase chain reaction quantitative real time (qPCR) of 10 RG (
G6PD
,
B2M
,
GUSB
,
HSP90
,
EF1A
,
RPLP0
,
GAPDH
,
ACTB
,
18 S
and
HPRT1
) to assess their suitability in OP analysis by using GeNorm, Normfinder, BestKeeper and RefFinder programs. A minimal number of two RG was recommended by GeNorm to obtain a reliable normalization.
RPLP0
and
B2M
were identified as the most stable genes in OP studies while
ACTB
,
18 S
and
HPRT1
were inadequate for normalization in our data set. Moreover, we showed the dramatic effects of suboptimal RG choice on the quantification of a target gene, highlighting the importance in the identification of the most appropriate reference gene to specific diseases. We suggest the use of
RPLP0
and
B2M
as the most stable reference genes while we do not recommend the use of the least stable reference genes
HPRT1
,
18 S
and
ACTB
in OP expression assays using PBMC as biological source. Additionally, we emphasize the importance of individualized and careful choice in software and reference genes selection.