This is not an argument of the present review that is limited only to QUS measurement in children. At any rate, the results are very encouraging for a future clinical use of some QUS methods in term and preterm newborns. Few studies have shown comparison data between two or more skeletal sites by using the same or different QUS methods in children.
Lequin et al. Schonau et al. The different bone components at the ROI Table 1 could explain, at least in part, these divergent results. Studies in healthy children and in patients with disturbances of growth, disorders of bone and mineral metabolism, or chronic diseases have shown a wide range of correlation between QUS variables measured at the heel 17 , 18 , 27 , 28 , 57 , 60 , 67 , proximal phalanges of the hand 29 , 30 , 83 , 84 , midshaft tibia or distal third of the radius 58 , 85 and central, peripheral, or total body BMD assessed by DXA.
These data confirm that QUS and DXA provide different information on bone tissue as they are influenced by different factors. The growing knowledge on the physical mechanisms related to the ultrasound characterization of bone tissue and the clinical application of QUS methods have shown that these techniques are a useful tool to assess integral bone mineral status and fracture risk in children. Although QUS devices are based on a similar technology, they differ among them for the skeletal site of measurement, performance, accuracy, measured QUS variables, and normative data.
Bone quantitative ultrasound
Large databases according to the main anthropometric findings from early childhood to young-adulthood are needed for a correct interpretation of the results in clinical setting. The simplicity of use that requires, however, an adequate training of the operators of the QUS devices, the lack of radiation exposure for the child, the possibility to perform the examination at bedside, and the low cost represents clear advantages of QUS methods compared with x-ray-based densitometric techniques, as DXA and pQCT.
However, too few comparative data on the estimation of fracture risk by using these methods are available in children to define which is the best among them for this purpose. Paediatr Drugs 7 : — Appl Radiat Isot 50 : — Baroncelli GI, Saggese G Critical ages and stages of puberty in the accumulation of spinal and femoral bone mass: the validity of bone mass measurements. Horm Res 54 : 2—8. Arch Dis Child 88 : — Eur Radiol 13 : — Specker BL, Schoenau E Quantitative bone analysis in children: current methods and recommendations.
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J Pediatr : — J Bone Miner Res 11 : — Osteoporos Int 7 : 7— Osteoporos Int 7 : 89— J Bone Miner Res 8 : — A reflection. Osteoporos Int 12 : 1— Calcif Tissue Int 64 : 18— J Bone Miner Res 15 : — Osteoporos Int 13 : 55— Osteoporos Int 6 : — Bone 39 : — Calcif Tissue Int 56 : — Osteoporos Int 8 : — Osteoporos Int 16 : — The Phalangeal Osteosonogrammetry Study Group.
Osteoporos Int 13 : — Pediatr Res 49 : — Calcif Tissue Int 64 : 24— J Clin Densitom 3 : 1—7. Osteoporos Int 11 : — J Clin Densitom 4 : — Brukx LJ, Waelkens JJ Evaluation of the usefulness of a quantitative ultrasound device in screening of bone mineral density in children. Ann Hum Biol 30 : — J Clin Densitom 2 : — Pediatr Res 54 : — Osteoporos Int 8 : 16— Osteoporos Int 12 : — Br J Radiol 75 : 59— J Bone Miner Metab 20 : — Calcif Tissue Int 72 : — J Bone Miner Res 19 : — Wuster C, de Terlizzi F, Becker S, Cadossi M, Cadossi R, Muller R Usefulness of quantitative ultrasound in evaluating structural and mechanical properties of bone: comparison of ultrasound, dual-energy X-ray absorptiometry, micro-computed tomography, and mechanical testing of human phalanges in vitro.
Technol Health Care 13 : — Osteoporos Int 12 : 28— J Clin Densitom 3 : — Clin Nutr 23 : 89— Correlation with nutrition, puberty, anthropometry, and physical activity. J Clin Epidemiol 56 : — Bone 36 : — Ultrasound Med Biol 32 : — Zadik Z, Price D, Diamond G Pediatric reference curves for multi-site quantitative ultrasound and its modulators.
Osteoporos Int 14 : — J Adolesc Health 39 : — Bayer M, Kutilek S Ultrasound transmission through the os calcis in children: which side should we measure?. Calcif Tissue Int 61 : — Arch Dis Child 76 : — Calcif Tissue Int 67 : — Osteoporos Int 18 : — Halaba ZP, Pluskiewicz W Quantitative ultrasound in the assessment of skeletal status in children and adolescents.
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Ultrasound Med Biol 30 : — J Clin Endocrinol Metab 89 : — Pluskiewicz W, Pyrkosz A, Drozdzowska B, Halaba Z Quantitative ultrasound of the hand phalanges in patients with genetic disorders: a pilot case-control study. Calcif Tissue Int 67 : 19— Its prevalence is increasing due to the ageing of the population [ 2 ]. Osteoporosis is characterized by a deterioration of bone tissue microarchitecture that leads to low bone mineral density BMD and an increased risk of bone fragility fractures [ 3 ].
As occurs in many complex diseases, it is widely accepted that osteoporosis individual susceptibility is determined by the interaction of multiple genetic variants and environmental factors [ 4 , 5 ]. An important determinant of osteoporosis risk later in life is the peak bone mass PBM [ 6 ].
Enhancing bone mass accrual to maximize PBM, which is attained by early adulthood, could help in the elderly to reduce the risk of fracture [ 6 ]. Therefore, identifying genetic factors affecting bone mass in early adulthood would be worthwhile.
[Bone quantitative ultrasound].
QUS provides information about bone mass and other quality aspects which may be of relevance in determining fracture risk such as bone microstructure, elasticity or connectivity [ 11 , 12 ]. Besides this, previous studies have shown the ability of heel QUS to predict independently fracture risk [ 11 , 13 ]. Compared to dual-energy x-ray absorptiometry DXA , QUS is more easily accessible, low-cost, non-invasive and non-ionizing [ 14 ]. To identify the genetic factors underlying osteoporosis susceptibility, extensive genetic studies have been conducted reporting association of several genetic variants with different bone phenotypes [ 15 , 16 , 17 , 18 ].
However, these explain little of the heritability in complex phenotypes [ 19 ]. The missing heritability problem refers to the observation that the number of significant associations discovered does not form a substantial proportion of heritability for most traits. Thus, SNP-SNP interactions could help explain the missing heritability of common complex traits and therefore, their identification is considered of relevance. To date, only a few studies have been performed to identify SNP-SNP interactions influencing osteoporosis-related traits [ 20 , 21 , 22 , 23 , 24 , 25 , 26 ].
Taking into consideration all this evidence, and bearing in mind that it is likely that interactions of common variants at different loci are influencing QUS traits, the aim of this study was to identify SNP-SNP interactions between SNPs independently associated with QUS, that could contribute to QUS traits variation in early adulthood. Local ethics committees approved the study that was conducted following the Declaration of Helsinki. Were excluded from the study those individuals who reported therapy with hormonal contraceptives, diseases of metabolic or endocrine systems and history of bone disease.
During the interviews and for a better precision of the food records, pictorial food models and standard household measures were used. This localization was selected on the basis of its accessibility and its high content of trabecular bone [ 32 ]. To guarantee the long-term stability of the ultrasound bone densitometer, daily calibrations were performed using a with physical phantom. The amplification reaction was performed following the conditions recommended by the manufacturer. The accuracy of the genotyping process was verified including in all plates negative controls and duplicate samples.
For all analyses the genotype of each SNP was encoded as 0, 1, 2, where 0 and 2 denotes homozygotes with major allele and minor allele respectively and 1 codes heterozygotes. Linear regression analyses were adjusted for the following covariates: sex, age, BMI, physical activity and calcium intake.
To all associations, the highly conservative Bonferroni correction considering the number of tested SNPs was applied. The characteristics of the study subjects have been published previously [ 28 ]. In this study, we aimed to provide a more comprehensive view of the genetic architecture underlying QUS by analysing two-way interactions between common SNPs in candidate genes. A number of SNPs in candidate genes were analysed considering potentially important covariates for bone mineralization process such as, age, sex, calcium intake, physical activity and BMI.
Even though these data suggest that epistatic SNP-SNP interactions does not influence heel ultrasound measurements in young Caucasian adults, the possibility of a false negative due to a limited statistical power cannot be excluded. The positive effects of the oestrogens on the skeleton have been well established; oestrogens play a major role in the aetiology of osteoporosis by the regulation of bone turnover and inhibition of bone loss [ 34 ].
The rs variant is located in the first intron of the ESR1 gene and although this intron may contain regulatory elements, the functional implication of this genetic variant remains unknown. In addition, low-density lipoprotein receptor-related protein 5 LRP5 codifies a protein belonging to the Wnt canonical signal, which regulates osteoblast and osteocyte function [ 36 ]. The results of this study could be suggestive of a well-regulated cross-talk between ESR1 and LRP5 genes in bone physiology.
Although ESR1 and LRP5 develop different roles in skeletal homeostasis, they could be interacting in bone cell biology through synergistic or antagonistic actions. It could be hypothesised that individuals carrying risk alleles at rs and rs SNPs have a lower expression of both ESR1 and LRP5, which could lead to an impaired bone mass. As we have analysed a cohort including only young adults, our findings also may suggest that the interaction between rs and rs SNPs might be implicated in bone mass accrual. Although previous studies have reported the individual contribution of these polymorphisms to osteoporosis-related phenotypes in early adulthood [ 30 , 38 , 39 , 40 , 41 ], the molecular mechanisms through which these polymorphisms might interact are still under investigation.
Future studies are required to elucidate the molecular mechanisms by this interaction is implicated in the bone mass acquisition process during early adulthood. Interestingly, all of these genes belong to well characterize pathways implicated in the complex mechanisms that regulate bone formation.
Thus, a novel line of research would be very interesting to elucidate how they may be interacting at the molecular level.
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- Analysis of SNP-SNP interactions and bone quantitative ultrasound parameter in early adulthood!
Thus, beyond the individual effect of SNPs in a gene, epistatic SNP-SNP interactions in the same gene occur and could be a potential factor contributing to the unexplained heritability of bone mass acquisition. Thus, a limitation of the present study could be the population size included that would not reach enough statistical power to detect epistatic SNP-SNP interactions with weak effect. Therefore, in order to support our preliminary results, further studies including larger population size and meta-analysis are needed.
Aino Hospital, Osaka, Japan. Izumiotsu Municipal Hospital, Osaka, Japan. TM Clinical Support Co. Find all citations in this journal default. Or filter your current search. Journal of Medical Ultrasonics [07 Sep , 45 1 ]. On the other hand, quantitative ultrasound QUS is widely used to assess bone density as part of medical screening as it is relatively inexpensive and easy to perform.
Current QUS devices do not share precise ultrasound-related parameters, such as frequency, waveform, beam pattern, transient response, definition of propagation time, definition of degree of attenuation, and precise measurement site, resulting in different measurements across models.
This has made it possible to convert QUS measurements from different models into standardized values, greatly improving the effectiveness of QUS measurements. Read Article at publisher's site.
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