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There is no single factor that causes acute anterior cruciate ligament (ACL) injuries. ACL ruptures are therefore considered multifactorial conditions with evidence from both familial and case-control genetic association studies that DNA sequence variants play an important role in its etiology. A growing number of common variants within genes encoding proteins, such as collagens, fibrillins, and proteoglycans, involved in the structure and regulation of the formation of the basic building block of the ACL (namely, the collagen fibril), have been associated with ACL rupture. In addition, variants within genes coding for proteins involved in biological processes responsible for ligament remodeling, adaptation, and repair have also recently been associated with the risk of ACL rupture. Recently, variants within collagens and other genes encoding other ligament-associated proteins have also been associated with altered risk of the canine ACL via cranial cruciate ligament rupture, strengthening the hypothesis that DNA sequence variants play an important role in the etiology of ligament injuries.
This chapter will review our current understanding and future research directions in elucidating the genetic influences on ACL rupture. Molecular genetics is one of several scientific disciplines researchers can apply to explore the biological mechanisms of ACL ruptures. Finally, the clinical application of this area of investigation will briefly be reviewed in this chapter.
The effective clinical management and prevention of ACL ruptures is most likely hinged on how rapidly we improve our current understanding of the dynamic relationship between the biomechanical and biological mechanisms underpinning ACL injury susceptibility. It is therefore imperative that clinicians and scientists understand both clinical and scientific terminology in order to facilitate the depth of research into the biological mechanisms of ACL ruptures. The next section will define some of the basic concepts in human molecular genetics.
Human beings are not identical; there are both visible and measurable normal biological variations among us, which contributes to each person being unique. Part of this biological variation is caused by common DNA sequence variations, known as polymorphisms, found within the three billion base pairs of the human genome. The human genome, which is 99.9% identical across all people, consists of approximately 19,000 coding genes (e.g., COL1A1 ) from which proteins (e.g., COL1A1 encodes for the α1(I) chain of type I collagen) are produced, representing the complete set of human genetic information, stored as DNA sequences ( Fig. 2.1 ). Although changes in the DNA sequence, usually referred to as mutations, can cause human disease, most DNA sequence changes are not considered deviations from the normal sequence, but rather are normal sequence alternatives. For example, recognised is also an acceptable alternative spelling for recognized . In this case, these polymorphisms do not cause severe diseases but potentially can modulate disease and/or injury susceptibility. Biologists have exploited the sequence differences noted between individuals (individual polymorphisms) to map susceptibility loci underlying common disease. Often, a combination of contiguous polymorphisms and their specific alleles are used to identify genetic intervals of inclusion or exclusion, and this is referred to as haplotype analyses (inheritance of a set of alleles representing a chromosomal position).
Interindividual variations in physical characteristics (phenotypes), such as height and the response of maximal oxygen uptake to training, are determined in part by polymorphisms. It is therefore reasonable to propose that these polymorphisms also contribute to biological variation in the structure and function of tissues such as the ACL. The response of the ACL to load (training), susceptibility of the ACL to rupture, as well as the repair and healing of the ACL is therefore not identical among individuals. If we accept that polymorphisms contribute to a lesser or greater extent to normal biological variation, genes encoding proteins involved in ACL structure and function are therefore plausible candidates to be tested for association with risk of ACL rupture (as indicated in O’Connell et al.).
Although there are important limitations to the approach that need to be considered, all the published studies to date reporting an association of DNA sequence variants with ACL ruptures in humans have used a case-control candidate gene approach (reviewed in September et al.). A well-designed genetic association study should be sufficiently powered (sample size) and contain well-defined unrelated cases with similar environmental exposures and appropriately matched healthy and injury-free, unrelated controls. The diagnostic criterion used in the clinical diagnoses of the cases should be the same or very similar for all cases. Furthermore, the inclusion and exclusion criteria for the study need to be carefully considered and defined. For example, the mechanism of injury, such as noncontact or contact, is an important factor when recruiting participants with a history of an ACL rupture as cases. Those with no history of ligament injuries, the controls, should also be relatively healthy and need to be matched for ancestry (country of birth), age, weight, gender, level of sport participation (higher or equal), and other intrinsic and extrinsic factors known to associate with ACL rupture. The candidate gene selected for the association study should be based on an a priori hypothesis that the gene product (e.g., type I collagen) is directly involved in the etiology of ACL ruptures. DNA samples extracted from tissue (usually blood samples or buccal cells) donated by the cases and controls are genotyped for potentially informative polymorphisms (e.g., rs1800012) within the candidate gene (e.g., COL1A1 ) (see Fig. 2.1 ). The necessary experimental quality control measures need to be taken to ensure reliability and accuracy in the generation of the genotyping data and need to be reported. Finally, investigators will determine whether any of the genotypes (e.g., GG, GT, or TT for COL1A1 rs1800012) or alleles (G or T) are significantly associated with ACL ruptures using appropriate statistical analyses. The data should always be interpreted with caution, taking into account the limitations and confounders of the study design.
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