Genome-wide linkage analysis of quantitative biomarker traits of osteoarthritis in a large, multigenerational extended family
Hsiang-Cheng Chen
Duke University Medical Center, Durham, North Carolina
Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
Drs. Chen and V. Kraus contributed equally to this work.
Search for more papers by this authorCorresponding Author
Virginia Byers Kraus
Duke University Medical Center, Durham, North Carolina
Drs. Chen and V. Kraus contributed equally to this work.
Box 3416, Duke University Medical Center, Durham, NC 27710Search for more papers by this authorYi-Ju Li
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSarah Nelson
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorCarol Haynes
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorJessica Johnson
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorThomas Stabler
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorElizabeth R. Hauser
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSimon G. Gregory
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorWilliam E. Kraus
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSvati H. Shah
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorHsiang-Cheng Chen
Duke University Medical Center, Durham, North Carolina
Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
Drs. Chen and V. Kraus contributed equally to this work.
Search for more papers by this authorCorresponding Author
Virginia Byers Kraus
Duke University Medical Center, Durham, North Carolina
Drs. Chen and V. Kraus contributed equally to this work.
Box 3416, Duke University Medical Center, Durham, NC 27710Search for more papers by this authorYi-Ju Li
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSarah Nelson
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorCarol Haynes
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorJessica Johnson
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorThomas Stabler
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorElizabeth R. Hauser
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSimon G. Gregory
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorWilliam E. Kraus
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorSvati H. Shah
Duke University Medical Center, Durham, North Carolina
Search for more papers by this authorAbstract
Objective
The genetic contributions to the multifactorial disorder osteoarthritis (OA) have been increasingly recognized. The goal of the current study was to use OA-related biomarkers of severity and disease burden as quantitative traits to identify genetic susceptibility loci for OA.
Methods
In a large multigenerational extended family (n = 350), we measured 5 OA-related biomarkers: hyaluronan (HA), cartilage oligomeric matrix protein (COMP), N-propeptide of type IIA collagen (PIIANP), C-propeptide of type II procollagen (CPII), and type II collagen neoepitope (C2C). Single-nucleotide polymorphism markers (n = 6,090) covering the whole genome were genotyped using the Illumina HumanLinkage-12 BeadChip. Variance components analysis, as implemented in the Sequential Oligogenic Linkage Analysis Routines, was used to estimate heritabilities of the quantitative traits and to calculate 2-point and multipoint logarithm of odds (LOD) scores using a polygenic model.
Results
After adjusting for age and sex, we found that 4 of the 5 biomarkers exhibited significant heritability (PIIANP 0.57, HA 0.49, COMP 0.43, C2C 0.30; P ≤ 0.01 for all). Fourteen of the 19 loci that had multipoint LOD scores of >1.5 were near to or overlapped with previously reported OA susceptibility loci. Four of these loci were identified by more than 1 biomarker. The maximum multipoint LOD scores for the heritable quantitative biomarker traits were 4.3 for PIIANP (chromosome 8p23.2), 3.2 for COMP (chromosome 8q11.1), 2.0 for HA (chromosome 6q16.3), and 2.0 for C2C (chromosome 5q31.2).
Conclusion
Herein, we report the first evidence of genetic susceptibility loci identified by OA-related biomarkers in an extended family. Our results demonstrate that serum concentrations of PIIANP, HA, COMP, and C2C have substantial heritable components, and using these biomarkers, several genetic loci potentially contributing to the genetic diversity of OA were identified.
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