Onychocryptosis Is Associated with Low Income in a Matched Cohort Study Using the All of Us Database.

Introduction: Onychocryptosis is a common and often painful nail condition, but risk factors have been relatively unexplored. We aimed to analyze associations between onychocryptosis, comorbidities, and income level. Methods: Using the National Institute of Health All of Us Research Program Database, a matched case-control study was performed for patients with onychocryptosis diagnosis and comorbidities and lifestyle factors. Results: A total of 6,246 cases of onychocryptosis and 24,984 controls were analyzed. Patients with onychocryptosis versus controls had increased risk of onychogryphosis (OR 5.66; 95% CI 4.87, 6.58), onychomycosis (2.63; 2.06, 3.36), hallux valgus (1.68; 1.50, 1.87), type 2 diabetes mellitus (1.49; 1.40, 1.60), obesity (1.38; 1.30, 1.48), and peripheral vascular disease (1.24; 1.14, 1.35) compared to controls. Patients who reported living in low-income households more often had onychocryptosis (reference group annual income >200 k; annual income <10 k USD, OR: 1.76; 95% CI: 1.46, 2.12, p < 0.001 vs. annual income 150-200 k USD, OR: 1.26; 95% CI: 0.99, 1.61, p = 0.06). Conclusion: Low income, obesity, PVD, and T2DM were associated with onychocryptosis diagnosis. It is recommended that these at-risk populations be screened for onychocryptosis and counseled on proper nail trimming techniques. Future studies are needed to examine the relationship between household income and onychocryptosis risk.

Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program.

OBJECTIVE: The All of Us Research Program (All of Us) aims to recruit over a million participants to further precision medicine. Essential to the verification of biobanks is a replication of known associations to establish validity. Here, we evaluated how well All of Us data replicated known cigarette smoking associations. MATERIALS AND METHODS: We defined smoking exposure as follows: (1) an EHR Smoking exposure that used International Classification of Disease codes; (2) participant provided information (PPI) Ever Smoking; and, (3) PPI Current Smoking, both from the lifestyle survey. We performed a phenome-wide association study (PheWAS) for each smoking exposure measurement type. For each, we compared the effect sizes derived from the PheWAS to published meta-analyses that studied cigarette smoking from PubMed. We defined two levels of replication of meta-analyses: (1) nominally replicated: which required agreement of direction of effect size, and (2) fully replicated: which required overlap of confidence intervals. RESULTS: PheWASes with EHR Smoking, PPI Ever Smoking, and PPI Current Smoking revealed 736, 492, and 639 phenome-wide significant associations, respectively. We identified 165 meta-analyses representing 99 distinct phenotypes that could be matched to EHR phenotypes. At P < .05, 74 were nominally replicated and 55 were fully replicated. At P < 2.68 × 10-5 (Bonferroni threshold), 58 were nominally replicated and 40 were fully replicated. DISCUSSION: Most phenotypes found in published meta-analyses associated with smoking were nominally replicated in All of Us. Both survey and EHR definitions for smoking produced similar results. CONCLUSION: This study demonstrated the feasibility of studying common exposures using All of Us data.