Table 12: List of associations between abnormal radiological morphological charactertistics of hip shape and OA. Radiological Morphological Characteristic Study Design Value associated with risk Definition of OA Risk of developing OA Association with OA Lateral Angle (LCEA) Longitudinal case series, 4-29 year f/up, n=18 (20-35 yrs of age), no OA at baseline <20 ROA All developed OA (Wiberg, 1939) Longitudinal case series, n=32 hips (age average 43 yrs), no OA at baseline, f/up 22 years <20 ROA All developed OA (Cooperman et al. 1983) Longitudinal cohort study, cases (n=74, OA before age 65) versus controls (n=43, no OA before age 65). <16 KL≥2 No controls had a LCEA < 16 (Murphy et al. 1995) Cross-sectional cohort study, cases (n=566, all with unilateral OA) versus controls (n=1108, no OA). Measurements taken from non-degenerate hip for cases. <20 minJSW≤ 2.5mm OR[95%CIs] = 10.1[2.9-35] (McWilliams et al. 2010) Longitudinal cohort study, cases (n=58, developed OA by 8 years) versus controls (n=118, did not develop OA), all females (mean age 70 years), f/up 8 years. <30 ROA OR[95%CIs] = 3.3[1.1-10.1] (Lane et al. 2000) Longitudinal cohort study, cases (n= 78, developed OA) versus controls (n=757, no OA), mean age 65 years, mean f/up 6.6 years <25 KL≥2 OR[95%CIs] = 2.4[1.2-4.7] (Reijman et al. 2005) Cross-sectional study, cases (presence of ROA) versus controls (no ROA), n=3859 total individuals. <20 KL≥2 OR[95%CIs] = 3.2[1.7-5.9] (Jacobsen et al. 2005) Edge
independent case-control studies, limiting the eventual associations to those with the lowest p-values in the discovery study (Hoover, 2007) The selection of study participants is vital. Case misclassification can dilute the power of a study and prejudice the outcome toward no association. In addition, as shown in the large-scale GWAS of the highly heterogenous disease OA, the investigation of stratified, homogenous endophenotypes, are likely to lead to an increased number of genetic discoveries underpinning disease development (Panoutsopoulou and Zeggini, 2013). Selection of genotyping platform (technology used to assay the genotypes of the study participants) is influenced by; the number of SNPs to be examined, the available budget, resources, and sample size. The ideal platform combines high throughput and accuracy with low cost per SNP analysis (Kwok, 2001; Syvänen, 2001). Many platforms exist, with several being able to genotype millions of sites simultaneously, for example, the Illumina Inc. BeadArray technology (Shen et al. 2005). BeadArray technology combines a miniaturized array platform with a high level of assay multiplexing and scalable automation. 1.4.6: Meta-analysis and Replication Almost all of what we presently know about the genetics of human polygenic disorders and quantitative traits has derived from meta-analysis of genome-wide association data (Panagiotou et al. 2013). Meta-analysis is defined as a statistical method, which allows the quantitative synthesis of results from different studies in order to estimate a common summary effect (Lau et al. 1997). The need for large sample sizes meant that meta-analysis of GWAS data from different studies was recognized as the appropriate method to achieve adequate sample sizes and optimal power for the discovery of genetic associations with modest effect sizes (Evangelou et al. 2007; Skol et al. 2007). of multiple GWAS datasets is now a well-established and validated strategy for both discovery and replication of genetic association studies (Skol et al. 2007).
of anatomical joint involvement and bone remodelling responses to the disease, each with differing genetic contributions. Disease heterogeneity reduces the statistical power to detect genetic association and greatly decreases the estimates of risk attributed to genetic variation (Manchia et al. 2013). As the degree of heterogeneity increases (defined as the presence of “non-cases” within a case population), so does the minimum sample size required to achieve sufficient statistical power. For example, heterogeneity of 50% increases the required sample size by approximately three times (Manchia et al. 2013). In psychiatric disorders, the strategy of studying more homogenous sub-groups of individuals has been shown to significantly decrease the number of cases needed for adequately powered genetic studies (Jaitovich-Groisman & Cruceanu 2010; Davies 1986). Similarly, the investigation of the quantitative trait bone mineral density (BMD) in a GWAS for osteoporosis, confirmed substantial increases in power gained as a result of utilising a phenotype closer to the underlying biology of the disease (Estrada et al. 2012). Fifty-six loci associated with BMD at genome-wide significance, whereas only 6 associated at that same theshold with a clinical history of fracture (Estrada et al. 2012). Therefore, in spite of an inherent loss of sample size, the study of more homogenous, narrower phenotypes, contiguous with the biology of a disease, has the potential to lead to the discovery of many more variants behind individual mechanisms of disease development and progression. In addition, the effect sizes of those marginally significant variants identified in GWAS may be larger if they were examined in more homogeneous samples (Manchia et al. 2013; Evangelou et al. 2011), further closing the gap of missing heritability. 1.5: The Genetic Aetiology of Osteoarthritis Twin studies estimate the genetic contribution to susceptibility of radiographic OA at the hip and knee in women is between 39% and 70% (MacGregor et al. 2008). Strength of heritability is site-specific with hand and hip OA more heritable than knee OA (MacGregor et al. 2008; Loughlin, 2005). Individual radiographic features of OA (e.g. osteophytes and joint space narrowing) differ in their heritability both within and
Inferior Acetabular Osteophyte (Absent/Present) 50 Absent=64%; Present=36% 0.60 0.37 Bombelli Classification 50 Nor=61%; Hyp=23%; Atr=16% 0.56 0.41 Acetabular Subchondral Cyst (Absent/Present) 50 Absent=66%; Present=34% 0.74 0.56 Femoral Head Subchondral Cyst (Absent/Present) 50 Absent=43%; Present=57% 0.62 0.36 Acetabular Sclerosis (Absent/Present) 50 Absent=69%; Present=31% 0.56 0.49 Femoral Head Sclerosis (Absent/Present) 50 Absent=68%; Present=32% 0.40 0.55 Femoral Head Flattening (Absent/Present) 50 Absent=59%; Present=41% 0.79 0.77 Table 34: Kappa coefficient result interpretation table. Kappa Agreement 0 0.01-0.2 0.21-0.4 0.41-0.6 0.61-0.8 0.81-0.99 Less than chance Slight Fair Moderate Substantial Almost perfect
Table 35: Results of knee OA repeatability studies Knee OA Variable (grading system) N Prevalence per variable grade (%) Intra-Kappa score (k) Inter-Kappa score (k) Joint Space Narrowing (JSN) Lateral OARSI photographic atlas (0-3) 50 0=42%; 1=24%; 2=15%; 3=19% 0.7 0.29 Medial OARSI photographic atlas (0-3) 50 0=40%; 1=14%; 2=16%; 3=30% 0.7 0.49 Lateral LDA JSN atlas (-1-5) 50 -1=10%; 0=44%; 1=10%; 4=8%; 5=28% 0.46 0.35 Medial LDA JSN atlas (-1-5) 50 0=36%; 1=12%; 3=8%; 4=14%; 5=30% 0.63 0.33 PFJ Joint space narrowing (0-3) (Lateral view) 50 0=60%; 1=23%; 2=7%; 3=10% 0.45 0.44 PFJ Lateral facet JSN LDA atlas (-1-5) (Skyline view) 50 0=72%; 1=7%; 2=5%; 3=3%; 4=5%; 5=8% 0.63 0.45 PFJ Medial facet JSN LDA atlas (-1-5) (Skyline view) 50 -1=2%; 0=77%; 1=7%; 2=5%; 3=5%; 5=4% 0.41 0.23 Osteophyte Grade (OARSI atlas) Lateral femoral condyle osteophyte size (0-3) 50 0=39%; 1=27%; 2=12%; 3=22% 0.45 0.26
Table 54: Summary statistics of the associated variants before and after adjustment for sex, height and body mass index in the first set of arcOGEN cases. SNP Cases Definition Controls definition N case/control P P_adjusted rs754106 Hip OA with superior JSN Hip OA with non-superior JSN 1234/525 4.10 x10-6 5.25 x10-5 rs754106 Hip OA with axial/medial JSN Hip OA with non-axial/medial JSN 404/1355 1.05 x10-5 1.75 x10-4 rs73023563 Hip OA with superior JSN Hip OA with non-superior JSN 1234/525 2.34 x10-7 1.80 x10-7 rs17050727 Hip OA with axial/medial JSN Hip OA with non-axial/medial JSN 1234/525 4.35 x10-5 4.68 x10-5 rs73023563 Hip OA with axial/medial JSN Hip OA with non-axial/medial JSN 404/1355 1.74 x10-6 1.14 x10-6 rs6766414 Hip OA with hypertrophic response Hip OA with non-hypertrophic response 518/1241 2.90 x10-5 3.19 x10-5 rs61837881 Hip OA with hypertrophic response Hip OA with non-hypertrophic response 518/1241 1.97 x10-4 2.37 x10-4
Table 55: Validation of top signals by Sequenom MassARRAY iPLEX Gold assay. amvnam, hip OA with axial/medial joint space narrowing vs. hip OA with non-axial/medial joint space narrowing; avna, hip OA with atrophic bone response vs. hip OA with non-atrophic response. Sequenom summary statistics GWAS summary statistics Concordance between Sequenom and GWAS SNP EA Stratum N case/control OR [95%CI] P EAF cases EAF controls OR [95%CI] P EAF cases EAF controls Imputation score % Genotype concordance % Minor allele concordance rs754106 T amvnam 413/1366 1.43 [1.21-1.68] 0.393 0.479 1.42 [1.21-1.67] 1.37x10-5 0.393 0.478 1 100 100 rs16869403 G avna 262/1517 2.05 [1.57-2.68] 0.170 0.092 2.11 [1.61-2.77] 2.36x10-7 0.164 0.088 0.97 99 97