J Clin Endocrinol Metab 83:3480–3486PubMed”
“Erratum to: Ost

J Clin Endocrinol Metab 83:3480–3486PubMed”
“Erratum to: Osteoporos Int DOI 10.1007/s00198-011-1804-x In the subsection Atypical femoral fractures / Pathophysiology / Suppression of bone turnover, the last word of the first paragraph selleck chemicals should have been “hypoparathyroidism”, not “hyperparathyroidism”. The sentence concerned should read “In osteosclerotic bone diseases due to decreased bone resorption, however, AFFs have not been reported, nor have they been described in other conditions associated with low bone turnover such as hypothyroidism or hypoparathyroidism.”

The author sincerely regrets any confusion that may have been caused.”
“Erratum to: Osteoporos Int DOI 10.1007/s00198-011-1608-z In the subsection “Cohort construction” under Methods, the first four sentences of the second paragraph should have read as follows: Since more than 95% of the osteoporosis patients revisited their physician for their osteoporosis drug prescriptions within 120 days during the study period, we excluded those who filled their prescription for any osteoporosis medication or had been assigned diagnosis codes for osteoporosis during the period January 1, 2005 to April 30, 2005. By doing this website so, we constructed a retrospective cohort with newly diagnosed osteoporosis

patients who had not taken any medications for osteoporosis. Patients who switched between bisphosphonate and any other medications

for osteoporosis were excluded from the study. Additionally, individuals who were diagnosed with cancer (Selleckchem KU57788 ICD-10 code: C-D), chronic renal failure Fenbendazole (ICD-10 code: N18), or atrial fibrillation (ICD-10 code: I48) prior to taking osteoporotic drugs were also excluded.”
“Introduction Genome-wide association studies (GWAS) provide a powerful approach to search for common genetic variants that increase susceptibility to complex diseases or traits. Nonetheless, they do not necessarily lead directly to the gene or genes in a given locus associated with disease, nor typically inform the broader context in which the disease genes operate. They thus provide limited insight into the mechanisms that drive disease. In addition, the amount of genetic variation explained by GWAS for a given disease is most often significantly less than the heritability estimate for the disease. For example, a number of studies estimate the genetic heritability for spine BMD to be as high as 80%, but the 15 genetic loci identified for spine BMD to date account for only ∼2.9% of the variation in spine BMD [1]. This raises the question of whether there are many more common DNA variants with smaller effects that are not being identified in the GWAS because of a lack of power, whether there are many more rare variants with stronger effect that explain the missing variation or whether it is some combination of these two scenarios.

Leave a Reply

Your email address will not be published. Required fields are marked *


You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>