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Background
Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analytical approaches from the Genetic Analysis Workshop 19 (GAW19). These contributions investigated both genome-wide association (GWA) and whole genome sequence (WGS) data from odd numbered chromosomes on up to 4 time points for blood pressure–related phenotypes. The statistical models used included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed-effect (LME), and variance components (VC). The goal of these analyses was to test statistical approaches that use repeat measurements to increase genetic signal for variant identification.Results
Two analytical methods were applied to the GAW19: GWA using real phenotypic data, and one approach to WGS using 200 simulated replicates. The first GWA approach applied a GEE-based model to identify gene-based associations with 4 derived hypertension phenotypes. This GEE model identified 1 significant locus, GRM7, which passed multiple test corrections for 2 hypertension-derived traits. The second GWA approach employed the LME to estimate genetic associations with systolic blood pressure (SBP) change trajectories identified using LCGM. This LCGM method identified 5 SBP trajectories and association analyses identified a genome-wide significant locus, near ATOX1 (p?=?1.0E?8). Finally, a third VC-based model using WGS and simulated SBP phenotypes that constrained the β coefficient for a genetic variant across each time point was calculated and compared to an unconstrained approach. This constrained VC approach demonstrated increased power for WGS variants of moderate effect, but when larger genetic effects were present, averaging across time points was as effective.Conclusion
In this paper, we summarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed techniques under alternative conditions for longitudinal genetic association. We conclude that these approaches when appropriately applied have the potential to: (a) increase statistical power; (b) decrease trait heterogeneity and standard error; (c) decrease computational burden in WGS; and (d) have the potential to identify genetic variants influencing subphenotypes important for understanding disease progression.Mechanical stimulation is commonly used in cartilage tissue engineering for enhancing tissue formation and improving the mechanical properties of resulting engineered tissues. However, expanded chondrocytes tend to dedifferentiate and lose expression of their primary cilia, which is necessary for chondrocyte mechanotransduction. As treatment with lithium chloride (LiCl) can restore passaged chondrocytes in monolayer, in this study, we investigated whether this approach would be effective in 3D culture and restore chondrocyte mechanosensitivity. Chondrocytes at different passages (P0 to P2) were treated with 0–50 mM LiCl for 24 h, with different pre-culture durations (0 to 4 days). The primary cilia incidence and length were measured in α-tubulin-stained images. Treated chondrocytes were cultured with or without dynamic compression to evaluate the effect of LiCl-induced primary cilia expression on matrix synthesis by mechanically stimulated chondrocytes. LiCl treatment of chondrocytes in 3D agarose culture increased primary cilia incidence and length, with significant increases in incidence and length using 50 mM LiCl compared to other concentrations (P?<?0.05). This effect was further optimized by including a 4-day pre-culture prior to the 24-h 50 mM LiCl treatment. Importantly, LiCl-induced primary cilia expression increased chondrocyte mechanosensitivity. When stimulated with dynamic compression, LiCl-treated P1 chondrocytes increased collagen (1.4-fold, P?<?0.1) and proteoglycan (1.5-fold, P?<?0.05) synthesis compared to untreated, unstimulated cells. The LiCl treatment method described here can be used to restore primary cilia in passaged chondrocytes, transforming them into a mechanosensitive cell source for cartilage tissue engineering.
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