Demographic and Clinical Factors Associated With Nonsurgical Osteoarthritis Treatment Among Patients in Outpatient Clinics

Objective

To identify patient demographic and clinical characteristics associated with osteoarthritis (OA) treatment use.

Methods

This was a secondary data analysis of 3 clinical trials among patients with hip or knee OA conducted in Duke Primary Care practices, the Durham Veterans Affairs (VA) Health Care System, and the University of North Carolina–Chapel Hill (UNC). At baseline, participants reported sociodemographic characteristics, OA‐related pain and function, and OA treatment use, including oral analgesics, topical creams, joint injections, and physical therapy. Separate, multivariable logistic models (adjusted for clustering of clinics and providers for the Duke and VA cohorts) were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the associations between participant characteristics and each type of OA treatment.

Results

Oral analgesic use was reported by 70–82% of participants across the 3 cohorts. Physical therapy, knee injections, and topical creams were used by 39–52%, 55–60%, and 25–39% of Duke, VA, and UNC participants, respectively. In multivariable models, worse pain, stiffness, and function, per 5‐unit increase, were associated with greater odds of using any oral analgesic for the cohorts from Duke (OR 1.18 [95% CI 1.08–1.28]) and UNC (OR 1.14 [95% CI 1.05–1.24]), but not for the VA cohort (OR 1.04 [95% CI 0.95–1.14]). For all 3 cohorts, nonwhites had higher odds of using topical creams compared to whites.

Conclusion

Results suggest potential underutilization of therapies other than oral analgesics. Patient characteristics may affect OA treatment use, and understanding the relationship between these factors and OA treatment preferences may improve adherence to OA treatment guidelines.     

Relationship Themes Present between Parents and Children in Recovery Homes

Approximately 12.5% of children have a parent with a substance use disorder. These children are likely to experience developmental delays, especially if they are placed into foster care. Oxford House recovery homes provide a useful setting that allows children to live with their parents after treatment for substance use. A sample of parents and their children who lived in Oxford Houses were interviewed, using mixed methods, and the outcomes suggest that Oxford Houses may provide a stable and supportive setting for parents and their children.     

Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

Local adaptation of climate-related traits in widespread temperate conifers has been demonstrated for centuries using extensive long-term common garden experiments (1, 2). As early as the 17th century, foresters were instructed to recognize variation in desirable traits and select seed from trees with favorable phenotypes (3). Modern tree improvement programs systematically select upon genetic variation, primarily to achieve growth gains and meet economic objectives. Estimates of genetic variation and gains from selection made using quantitative genetic models assume many anonymous loci of small effect underlie both variation in continuously distributed phenotypes and their responses to selective breeding. However, the type, quantity, effect size, distribution, and dynamics of genes underlying locally adaptive phenotypic variation and responses to selective breeding in forest trees are still poorly understood (4).Directional selection over hundreds or thousands of generations has led to genomic features of domestication in agricultural crops including simplified genetic architectures underlying many traits, reduced genome-wide diversity, and numerous selective sweeps (5–7). Beyond high-gain, short-rotation clonal forestry [e.g., Eucalyptus spp. (8)], we know little about the effects of artificial selection on adaptive genetic variation in forest trees, yet many tree species undergo some degree of selective breeding. Two or three generations of conifer breeding is not expected to have the same magnitude of genetic effects seen in domesticated crops, but if artificial selection for increased productivity is detectable in conifer genomes, it may expose genetic relationships and potential sources of trade-offs between growth and climatically adaptive phenotypes.Climate-related adaptive traits are often intercorrelated due to pleiotropy, natural selection, or linkage disequilibrium (LD), so that strong directional selection on one trait can cause correlated responses in others. Pleiotropic allelic variants associated with phenotypes do not function in isolation. Antagonistic pleiotropic effects among traits can generate adaptive trade-offs among traits within populations, and limit gains from selection on a focal trait (9). Trait–trait correlations can also arise through strong selection acting in parallel on unlinked loci or from LD mediated by physical linkage of loci on chromosomes. Average genome-wide LD estimates in conifers appear to be low (10, 11) but may be greater (r² of 0.2–0.4) within genes under strong selection (12).Conifer studies have identified putatively adaptive phenotype-associated alleles on a locus-by-locus basis using quantitative trait loci (QTL) mapping or genotype–phenotype associations (GPAs) (also known as genome-wide association studies [GWAS]) (13). Genotype–environment association analyses in conifers have identified putatively adaptive environmentally associated loci (e.g., 14, 15), but loci are usually anonymous relative to adaptive phenotypes. All of these approaches are biased toward detecting loci with large phenotypic effects, but expectations that genome scans will discover individual adaptive loci with large effects or frequency differences among populations may be biologically and statistically unrealistic (16, 17). Conifer GPA studies typically detect relatively few statistically significant loci, and locus-by-locus analyses are insufficient to characterize adaptive genome-wide variation associated with adaptive traits and signatures of selective breeding. Multilocus tests for adaptive polygenic signatures of selection have been developed (e.g., refs. 18 and 19), but significant limitations remain (reviewed in refs. 20 and 21).Uncertainty about the effects of selective breeding on adaptive genetic variation is layered upon expectations that forest trees will become maladapted as climates shift (22). Efforts are being made to estimate maladaptation using genome-wide variation associated with adaptive traits and climate (23, 24), because conserving, managing, and efficiently redeploying genetic variation associated with adaptive phenotypes will be a necessary element of strategies to mitigate the effects of shifting climates on forest resources (25). Assisted gene flow strategies in temperate and subboreal forests generally aim to move trees to cooler climates in anticipation of future warming, but trees must then contend with the increased short- to medium-term risk of maladaptation to damaging frost. This means cold tolerance is, perhaps surprisingly, an important trait when planning for warming climates.Genetic approaches have the potential to efficiently and accurately characterize local adaptation to climate. Understanding whether this potential can be realized in a technically robust and operationally feasible way, and whether selection for faster growth compromises genetic variation associated with phenotypic adaptation to climate, has far-reaching implications for developing effective assisted gene flow strategies that mitigate negative climate change impacts on forest health and timber production (26, 27). In this context, our research objectives are to 1) identify the genetic architecture of climate-related adaptive traits in interior lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.); 2) identify genome-wide effects of artificial selection for increased productivity on climate-related traits; and 3) assess the implications of genetic responses to selection for assisted gene flow strategies.Our study combines climatic data, genotype data from ∼50,000 lodgepole pine single-nucleotide polymorphisms (SNPs), and seedling phenotypic data for height, cold injury, growth initiation, and growth cessation traits. These data were collected from a seedling common garden that sampled reforestation seed lots from 105 natural populations and 20 breeding populations from across the species’ range in Alberta (AB) and British Columbia (BC), Canada (Fig. 1 and SI Appendix, Table S1). For each of the four traits, we identify range-wide GPAs using 929 seedlings from all 105 natural populations. Then for the 1% most strongly phenotype-associated SNPs, we examine how artificial selection within breeding populations has changed allele frequencies at individual SNP loci, within individual seedlings, populations (breeding zones), and three climatic regions (Fig. 1). Using elements from the approach of Turchin et al. (18), we study changes in frequency of the alleles that have a positive effect on adaptive traits (positive effect alleles [PEAs]). At each SNP locus, a PEA is the allele associated with increasing numeric values of the respective phenotype, determined in this case through GPA analyses in the natural seedling populations. PEAs reported here are associated with greater seedling height, greater cold injury, delayed growth initiation, and delayed growth cessation. To parse physical genetic linkage from allelic associations due to other causes, we compare LD estimated from our natural seedlings with estimates of recombination among haploid megagametophytes from a single maternal parent, where physical linkage is the only cause of LD. Integrating genetic, climatic, and phenotypic data gives us a robust basis to detect the effects of artificial selection on climate-related genotypes that are relevant to breeding and assisted gene flow strategies.Open in a separate windowFig. 1.Geographic origins of the natural and selected seedling populations sampled from across the range of lodgepole pine in Alberta (AB) and British Columbia (BC). Natural populations are represented by filled circles; selected seedling breeding zones are represented by filled polygons. The three climatic regions we used were AB, BC-Central, and BC-South. AB breeding zones are formally identified as A, B1, B2, C, J, and K1. BC-Central breeding zone abbreviations are as follows: BV, Bulkley Valley; CP, Central Plateau; and PG, Prince George. BC-South breeding zone abbreviations are as follows: EK, East Kootenay; NE, Nelson; and TO, Thompson–Okanagan. Reprinted from ref. 35, with permission from Elsevier.