Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.

Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.

Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations.

BACKGROUND: Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles. OBJECTIVES: Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles. METHODS: We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts. RESULTS: Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED. CONCLUSIONS: Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial.

BACKGROUND: Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health. OBJECTIVES: To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification. METHODS: In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs. RESULTS: After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP. CONCLUSIONS: Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study.

Health outcomes, such as body mass index and cholesterol levels, are known to be dependent on age and exhibit varying effects with their associated risk factors. In this paper, we propose a novel framework for dynamic modeling of the associations between health outcomes and risk factors using varying-coefficients (VC) regional quantile regression via K-nearest neighbors (KNN) fused Lasso, which captures the time-varying effects of age. The proposed method has strong theoretical properties, including a tight estimation error bound and the ability to detect exact clustered patterns under certain regularity conditions. To efficiently solve the resulting optimization problem, we develop an alternating direction method of multipliers (ADMM) algorithm. Our empirical results demonstrate the efficacy of the proposed method in capturing the complex age-dependent associations between health outcomes and their risk factors.

Utilization of Medicare's chronic care management services by primary care providers.

BACKGROUND: Medicare billing codes introduced in 2015 reimburses primary care providers for non-face-to-face, chronic care management (CCM) services rendered by clinical staff. PURPOSE: The purpose of this manuscript was to describe provider trends in billed CCM services and identify factors associated with CCM utilization. METHODS: Observational study using Medicare Public Use Files, 2015 to 2018. General, family, geriatric, and internal medicine physicians, nurse practitioners (NPs), and physician assistants (PAs) with billed primary care services were included. Multivariable analyses modeled associations between the CCM services and type of provider, adjusting for year, primary care services, practice, and patient characteristics. FINDINGS: Among 140,465 physicians and 141,118 NPs/PAs, CCM services increased each year, yet remained underutilized: 2% to 7% of physicians and 0.3% to 1.3% of NPs/PAs billed CCM in 2018. Increases in beneficiaries (p < .0001), percentage of dually enrolled (p = .0134), and primary care services (p < .0001) predicted higher CCM utilization. DISCUSSION: CCM utilization reflects practice-based efforts to improve patient access to care by enhancing care delivery.

Quantile forward regression for high-dimensional survival data.

Despite the urgent need for an effective prediction model tailored to individual interests, existing models have mainly been developed for the mean outcome, targeting average people. Additionally, the direction and magnitude of covariates' effects on the mean outcome may not hold across different quantiles of the outcome distribution. To accommodate the heterogeneous characteristics of covariates and provide a flexible risk model, we propose a quantile forward regression model for high-dimensional survival data. Our method selects variables by maximizing the likelihood of the asymmetric Laplace distribution (ALD) and derives the final model based on the extended Bayesian Information Criterion (EBIC). We demonstrate that the proposed method enjoys a sure screening property and selection consistency. We apply it to the national health survey dataset to show the advantages of a quantile-specific prediction model. Finally, we discuss potential extensions of our approach, including the nonlinear model and the globally concerned quantile regression coefficients model.

The relationship between gut microbiota and short chain fatty acids in the renal calcium oxalate stones disease.

The relationship of gut microbiota and calcium oxalate stone has been limited investigated, especially with no study of gut microbiota and short chain fatty acids (SCFAs) in nephrolithiasis. We provided Sprague Dawley rats of renal calcium oxalate stones with antibiotics and examined the renal crystals deposition. We also performed a case-control study by analyzing 16S rRNA microbial profiling, shotgun metagenomics and SCFAs in 153 fecal samples from non-kidney stone (NS) controls, patients with occasional renal calcium oxalate stones (OS) and patients with recurrent stones (RS). Antibiotics reduced bacterial load in feces and could promote the formation of renal calcium crystals in model rats. In addition, both OS and RS patients exhibited higher fecal microbial diversity than NS controls. Several SCFAs-producing gut bacteria, as well as metabolic pathways associated with SCFAs production, were considerably lower in the gut microbiota among the kidney stone patients compared with the NS controls. Representation of genes involved in oxalate degradation showed no significance difference among groups. However, fecal acetic acid concentration was the highest in RS patients with high level of urinary oxalate, which was positively correlated with genes involvement in oxalate synthesis. Administration of SCFAs reduced renal crystals. These results shed new light on bacteria and SCFAs, which may promote the development of treatment strategy in nephrolithiasis.

Building generalized linear models with ultrahigh dimensional features: A sequentially conditional approach.

Conditional screening approaches have emerged as a powerful alternative to the commonly used marginal screening, as they can identify marginally weak but conditionally important variables. However, most existing conditional screening methods need to fix the initial conditioning set, which may determine the ultimately selected variables. If the conditioning set is not properly chosen, the methods may produce false negatives and positives. Moreover, screening approaches typically need to involve tuning parameters and extra modeling steps in order to reach a final model. We propose a sequential conditioning approach by dynamically updating the conditioning set with an iterative selection process. We provide its theoretical properties under the framework of generalized linear models. Powered by an extended Bayesian information criterion as the stopping rule, the method will lead to a final model without the need to choose tuning parameters or threshold parameters. The practical utility of the proposed method is examined via extensive simulations and analysis of a real clinical study on predicting multiple myeloma patients' response to treatment based on their genomic profiles.

The Efficacy of Neoadjuvant Versus Adjuvant Therapy for Resectable Esophageal Cancer Patients: A Systematic Review and Meta-Analysis.

OBJECTIVE: Inconclusive results are available as to whether chemo/radiotherapy should be administered to resectable esophageal cancer patients before surgery (neoadjuvant therapy) or after surgery (adjuvant therapy). The paper, via a meta-analysis of effects of treatment modalities when administering chemo/radiotherapy, aims to systematically evaluate the effect of timing of chemo/radiotherapy and surgery. METHODS: We performed a systematic literature search for clinical trials of neoadjuvant and adjuvant therapy for patients with esophageal cancer. Using meta-analysis, we conducted direct and adjusted indirect comparisons of overall survival, complete resection rate (R0 resection), perioperative mortality, leakage rate and local recurrence in patients with resectable esophageal cancer. RESULTS: A total of 32 studies involving 7985 patients with esophageal cancer were included in the meta-analysis. Twenty-five randomized controlled studies indirectly compared neoadjuvant/adjuvant therapy with surgery alone, while five non-randomized controlled studies and two randomized controlled studies directly compared neoadjuvant with adjuvant therapy. Neoadjuvant therapy followed by surgery, compared with surgery along with adjuvant therapy, showed a significant overall survival advantage in our pooled analysis (HR 0.88; 95% CI 0.79-0.98). Directly compared with adjuvant therapy, neoadjuvant therapy demonstrated a lower local recurrence rate (OR 0.56; 95% CI 0.43-0.74) with low heterogeneity (I2 = 1%). Neoadjuvant therapy, comparing to surgery with or without adjuvant therapy, showed a significantly higher R0 resection rate (OR 2.86; 95% CI 2.02-4.04) with moderate heterogeneity (I2 = 38%) and no significant differences in postoperative anastomotic leakage (P = 0.50). However, neoadjuvant therapy, compared with surgery adjuvant therapy, significantly increased perioperative mortality in both direct and indirect comparisons (P < 0.01). CONCLUSIONS: We found that neoadjuvant therapy was associated with higher overall survival and R0 resection rate without increasing postoperative anastomotic leakage for patients with resectable esophageal cancer, whereas neoadjuvant therapy was associated with higher perioperative mortality after esophagectomy.

A network-based variable selection approach for identification of modules and biomarker genes associated with end-stage kidney disease.

AIMS: Intervention for end-stage kidney disease (ESKD), which is associated with adverse prognoses and major economic burdens, is challenging due to its complex pathogenesis. The study was performed to identify biomarker genes and molecular mechanisms for ESKD by bioinformatics approach. METHODS: Using the Gene Expression Omnibus dataset GSE37171, this study identified pathways and genomic biomarkers associated with ESKD via a multi-stage knowledge discovery process, including identification of modules of genes by weighted gene co-expression network analysis, discovery of important involved pathways by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, selection of differentially expressed genes by the empirical Bayes method, and screening biomarker genes by the least absolute shrinkage and selection operator (Lasso) logistic regression. The results were validated using GSE70528, an independent testing dataset. RESULTS: Three clinically important gene modules associated with ESKD, were identified by weighted gene co-expression network analysis. Within these modules, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed important biological pathways involved in ESKD, including transforming growth factor-ß and Wnt signalling, RNA-splicing, autophagy and chromatin and histone modification. Furthermore, Lasso logistic regression was conducted to identify five final genes, namely, CNOT8, MST4, PPP2CB, PCSK7 and RBBP4 that are differentially expressed and associated with ESKD. The accuracy of the final model in distinguishing the ESKD cases and controls was 96.8% and 91.7% in the training and validation datasets, respectively. CONCLUSION: Network-based variable selection approaches can identify biological pathways and biomarker genes associated with ESKD. The findings may inform more in-depth follow-up research and effective therapy.