Elevated Dietary Inflammation Among Supplemental Nutrition Assistance Program Recipients Provides Targets for Precision Public Health Intervention.

INTRODUCTION: The Supplemental Nutrition Assistance Program was designed to prevent food insecurity among low-income Americans and has been linked to improvements in pregnancy health, long-term child development, and criminal recidivism. However, the pursuit of food security does not ensure nutritional sufficiency, and the program has not improved diet quality or cardiometabolic mortality (i.e., heart disease, stroke, diabetes). In this study, longitudinal cohort data are used to identify by Supplemental Nutrition Assistance Program status the proinflammatory characteristics that predispose to chronic disease. METHODS: Between 2015 and 2018, annual 24-hour dietary recalls were conducted with 409 residents from low-income, urban neighborhoods in Columbus and Cleveland, Ohio (statistical analysis started in 2019). The Dietary Inflammatory Index was calculated. It provides empirically validated estimates of the internal inflammation that each diet should produce; higher Dietary Inflammatory Index scores have been associated with elevated inflammatory biomarkers. Finally, associations between Supplemental Nutrition Assistance Program and Dietary Inflammatory Index were evaluated, and dietary components that differed by Supplemental Nutrition Assistance Program status were identified. RESULTS: Supplemental Nutrition Assistance Program recipients had higher Dietary Inflammatory Index scores (+0.40, 95% CI=0.09, 0.70) and a consistently lower intake of 4 anti-inflammatory nutrients (dietary fiber, ß-carotene, magnesium, vitamin E) than nonrecipients. Vitamin D intake did not differ by Supplemental Nutrition Assistance Program status but was well below the Recommended Daily Allowance in this sample. CONCLUSIONS: Supplemental Nutrition Assistance Program recipients had elevated Dietary Inflammatory Index scores, implying higher diet-driven inflammation. This was due, in part, to low intake of 4 anti-inflammatory food components, which were higher yet still nutritionally insufficient among nonrecipients. Findings highlight specific nutritional targets for improving public health through dietary change.

Low Omega-3 intake is associated with high rates of depression and preterm birth on the country level.

Low circulating levels of long chain omega-3 polyunsaturated fatty acids (LC omega-3 PUFA) have been linked to major depressive disorder (MDD) and preterm birth (PTB), and prenatal depression associates with PTB. We therefore hypothesized that low Omega-3 intake would associate with higher MDD and PTB rates on the country-level. To test this hypothesis, we obtained country-level estimates for omega-3 intake, MDD prevalence, PTB rate, and per capita income for 184 countries in 2010. We then estimated the LC omega-3 PUFA levels that these intakes produce by accounting for direct consumption and the endogenous conversion of ingested plant-based precursors. Penalized splines indicated that MDD and PTB rates decreased linearly with increasing LC omega-3 PUFA, up to ~ 1000 mg/day for MDD and up to ~ 550 mg/day for PTB. Adjusted linear regression models below these thresholds revealed that a one standard deviation increase in LC omega-3 PUFA (380 mg/day) was associated with an MDD decrease of 5 cases/1000 people and a PTB decrease of 15 cases/1000 livebirths. In light of the extensive prior evidence on the individual-level, these findings indicate that low intake of LC omega-3 PUFA and its precursors may be elevating MDD and PTB rates in 85% of the countries studied.

Omega-3 polyunsaturated fatty acid intake norms and preterm birth rate: a cross-sectional analysis of 184 countries.

BACKGROUND: The preponderance of evidence now indicates that elevated long-chain omega-3 polyunsaturated fatty acid (LC omega-3 PUFA) intake is often associated with reduced risk of preterm birth (PTB). This conclusion is based on recent meta-analyses that include several studies that reported null findings. We probed the reasons for this heterogeneity across studies and its implications for PTB prevention using country-level data. METHODS: We analysed the relationship between national PTB rates (<37 weeks of gestation) and omega-3 PUFA intake norms from 184 countries for the year 2010. To estimate the total LC omega-3 PUFA levels (eicosapentaenoic acid [EPA]/docosahexaenoic acid [DHA]) that these norms produce we utilised a metric that accounts for (1) seafood-based omega-3 intake (EPA/DHA) and (2) plant-based omega-3 intake (alpha-linolenic acid [ALA]), ~20% of which is converted to EPA/DHA in vivo. We then assessed the shape of the omega-3-PTB relationship with a penalised spline and conducted linear regression analyses within the linear sections of the relationship. RESULTS: Penalised spline analyses indicated that PTB rates decrease linearly with increasing omega-3 levels up to ~600 mg/day. Income-adjusted linear regression analysis among the countries in this exposure range indicated that the number of PTBs per 100 live births decreases by 1.5 (95% CI 2.8 to 0.3) for each 1 SD increase in omega-3 intake norms (383 mg/day). CONCLUSIONS: Taken with prior evidence for a causal association on the individual level, our findings indicate that omega-3 PUFA deficiency may be a widespread contributing factor in PTB risk. Consideration of baseline omega-3 PUFA levels is critical in the design of future interventions.

Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients.

Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofloxacin, ethionamide, cycloserine, and pyrazinamide and calculated areas under the concentration-time curves from 0 to 24 h (AUC0-24). The patients were followed monthly for sputum culture conversion based on liquid cultures. The median duration of amikacin therapy was 184 (range, 28 to 866) days, at a median dose of 17.30 (range 11.11 to 19.23) mg/kg. Only 11 (39%) patients had sputum culture conversion during treatment; the rest failed. We utilized classification and regression tree analyses (CART) to examine all potential predictors of failure, including clinical and demographic features, comorbidities, and amikacin peak concentrations (Cmax), AUC0-24, and trough concentrations. The primary node for failure had two competing variables, Cmax of <67 mg/liter and AUC0-24 of <568.30 mg · h/L; weight of >41 kg was a secondary node with a score of 35% relative to the primary node. The area under the receiver operating characteristic curve for the CART model was an R(2) = 0.90 on posttest. In patients weighing >41 kg, sputum conversion was 3/3 (100%) in those with an amikacin Cmax of ≥67 mg/liter versus 3/15 (20%) in those with a Cmax of <67 mg/liter (relative risk [RR] = 5.00; 95% confidence interval [CI], 1.82 to 13.76). In all patients who had both amikacin Cmax and AUC0-24 below the threshold, 7/7 (100%) failed, compared to 7/15 (47%) of those who had these parameters above threshold (RR = 2.14; 95% CI, 1.25 to 43.68). These amikacin dose-schedule patterns and exposures are virtually the same as those identified in the hollow-fiber system model.

Bioinformatics challenges for genome-wide association studies.

MOTIVATION: The sequencing of the human genome has made it possible to identify an informative set of >1 million single nucleotide polymorphisms (SNPs) across the genome that can be used to carry out genome-wide association studies (GWASs). The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control, imputation and analysis issues including multiple testing. This work has been successful and has enabled the discovery of new associations that have been replicated in multiple studies. However, it is now recognized that most SNPs discovered via GWAS have small effects on disease susceptibility and thus may not be suitable for improving health care through genetic testing. One likely explanation for the mixed results of GWAS is that the current biostatistical analysis paradigm is by design agnostic or unbiased in that it ignores all prior knowledge about disease pathobiology. Further, the linear modeling framework that is employed in GWAS often considers only one SNP at a time thus ignoring their genomic and environmental context. There is now a shift away from the biostatistical approach toward a more holistic approach that recognizes the complexity of the genotype-phenotype relationship that is characterized by significant heterogeneity and gene-gene and gene-environment interaction. We argue here that bioinformatics has an important role to play in addressing the complexity of the underlying genetic basis of common human diseases. The goal of this review is to identify and discuss those GWAS challenges that will require computational methods.

Haplotype diversity in four genes (CLCNKA, CLCNKB, BSND, NEDD4L) involved in renal salt reabsorption.

OBJECTIVE: Differences exist among various populations with regards to hypertension prevalence, severity, progression and response to therapy. Such differences may be due to genetic or environmental factors. We characterized the genetic variation and haplotype diversity of four hypertension candidate genes (CLCNKA, CLCNKB, BSND, NEDD4L) in four different ethnic groups (Caucasian Americans, African-Americans, Han Chinese, and Mexican-Americans). METHODS: We genotyped 42 single nucleotide polymorphisms across the four genes in equal numbers of each ethnically defined population, then tested for linkage disequilibrium, computed allelic and haplotype frequencies, and compared data across the different ethnic groups. RESULTS: We identified significant genotype and allele frequency differences among ethnic groups. The strongest differences were observed between African-American and Mexican-Americans and between Caucasian and Mexican-Americans. In addition, haplotype blocks were defined for BSND, CLCNKA_B and NEDD4L in the four populations examined. Completely mismatched ('yin yang') haplotypes were also observed. We found that the number of inferred halpotypes varied gene to gene and in some instances between the populations for a given gene indicating substantial haplotype diversity. The haplotype diversity among the various ethnic populations observed in our study was greater than that reported in Perlegen database. CONCLUSIONS: Haplotype diversity in hypertension candidate genes has important implications for designing and evaluating candidate gene or genome-wide blood pressure association studies that consider these genes.

Genomics, nutrition, obesity, and diabetes.

PURPOSE: To present evidence of genetic and environmental interactions as they relate to nutrition, diabetes, and obesity. METHODS: A review of seminal literature related to genetics, obesity, and diabetes. FINDINGS: Multifactorial interactions are important in the development of nutrition-related disorders, but the challenge remains to explain how these interactions are expressed. Treating subpopulations of people might be important and useful to some extent at present, but in the future treating people of given genetic predispositions and other personal and environmental factors will have greater effects on quality-of-life indicators and life expectancies. CONCLUSIONS: Individualization coupled with multifactorial interactions will lead to new and more effective preventive and treatment modalities of nutrition-related disorders. With obesity and diabetes, genomics will bridge the traditional use of diet, exercise, and weight reduction with other environmental factors, ultimately leading to healthier lives.