The latest news from the GENOMOS study.

Most common age-related diseases such as osteoporosis, have strong genetic influences and therefore intense efforts are ongoing to identify the underlying genetic variants. Knowledge of these variants can help in understanding the disease process and might benefit development of interventions and diagnostics. Association studies have now become the standard approach to uncover the genetic effects of common variants. Yet, in all fields of complex disease genetics - including osteoporosis - progress in identifying these genetic factors has been hampered by often controversial results. Because of the complicated genetic architecture of the diseases and the small effect size for each individual risk alleles, this is mostly due to low statistical power and limitations of analytical methods. It is now recognised that association analysis followed by replication and prospective multi-centred meta-analysis is currently the best way forward to identify genetic markers for complex traits, such as osteoporosis. To accomplish this, large (global) collaborative consortia have been established that have large collections of DNA samples from subjects with a certain phenotype and that use standardized methodology and definitions, to quantify by meta-analysis the subtle effects of the responsible gene variants. The GENOMOS consortium has played such a role in the field of osteoporosis and has initially identified and refuted associations of well known candidate genes. This consortium is now expected to play an important role in validation of risk alleles coming from Genome Wide Association Studies (GWAS) for osteoporosis, some of which have just been published. Together with genetic studies on more rare syndromes, the GWA approach in combination with the GENOMOS consortium, is likely to help in clarifying the genetic architecture of complex bone traits such as BMD, and - eventually - in understanding the genetics of clinically relevant endpoints in osteoporosis, i.e., fracture risk. Such genetic insights will be useful in understanding biology and are likely to also find applications in clinical practice.