Identification of new genetic polymorphisms that alter the dietary requirement for choline and vary in their distribution across ethnic and racial groups

Effect alleles (alleles with a polymorphism that is associated with the effect being measured) in a small number of single-nucleotide polymorphisms (SNPs) are known to influence the dietary requirement for choline. In this study, we examined a much larger number of SNPs (n=200) in 10 genes related to choline metabolism for associations with development of organ dysfunction (liver or muscle) when 79 humans were fed a low-choline diet. We confirmed that effect alleles in SNPs such as the C allele of PEMT rs12325817 increase the risk of developing organ dysfunction in women when they consume a diet low in choline, and we identified novel effect alleles, such as the C allele of CHKA SNP rs7928739, that alter dietary choline requirements. When fed a low-choline diet, some people presented with muscle damage rather than liver damage; several effect alleles in SLC44A1 (rs7873937, G allele; rs2771040, G; rs6479313, G; rs16924529, A; and rs3199966, C) and one in CHKB (rs1557502, A) were more common in these individuals. This suggests that pathways related to choline metabolism are more important for normal muscle function than previously thought. In European, Mexican, and Asian Americans, and in individuals of African descent, we examined the prevalence of the effect alleles in SNPs that alter choline requirement and found that they are differentially distributed among people of different ethnic and racial backgrounds. Overall, our study has identified novel genetic variants that modulate choline requirements and suggests that the dietary requirement for choline may be different across racial and ethnic groups

Carbon flux bias estimation employing Maximum Likelihood Ensemble Filter (MLEF)

We evaluate the capability of an ensemble based data assimilation approach, referred to as Maximum Likelihood Ensemble Filter (MLEF), to estimate biases in the CO2 photosynthesis and respiration fluxes. We employ an off-line Lagrangian Particle Dispersion Model (LPDM), which is driven by the carbon fluxes, obtained from the Simple Biosphere - Regional Atmospheric Modeling System (SiB-RAMS). The SiB-RAMS carbon fluxes are assumed to have errors in the form of multiplicative biases. Our goal is to estimate and reduce these biases and also to assign reliable posterior uncertainties to the estimated biases. Experiments of this study are performed using simulated CO2 observations, which resemble real CO2 concentrations from the Ring of Towers in northern Wisconsin. We evaluate the MLEF results with respect to the 'truth' and the Kalman Filter (KF) solution. The KF solution is considered theoretically optimal for the problem of this study, which is a linear data assimilation problem involving Gaussian errors. We also evaluate the impact of forecast error covariance localization based on a new 'distance' defined in the space of information measures. Experimental results are encouraging, indicating that the MLEF can successfully estimate carbon flux biases and their uncertainties. As expected, the estimated biases are closer to the 'true' biases in the experiments with more ensemble members and more observations. The data assimilation algorithm has a stable performance and converges smoothly to the KF solution when the ensemble size approaches the size of the model state vector (i.e., the control variable of the data assimilation problem

Evidence for negative selection of gene variants that increase dependence on dietary choline in a Gambian cohort

Choline is an essential nutrient, and the amount needed in the diet is modulated by several factors. Given geographical differences in dietary choline intake and disparate frequencies of single-nucleotide polymorphisms (SNPs) in choline metabolism genes between ethnic groups, we tested the hypothesis that 3 SNPs that increase dependence on dietary choline would be under negative selection pressure in settings where choline intake is low: choline dehydrogenase (CHDH) rs12676, methylenetetrahydrofolate reductase 1 (MTHFD1) rs2236225, and phosphatidylethanolamine-N-methyltransferase (PEMT) rs12325817. Evidence of negative selection was assessed in 2 populations: one in The Gambia, West Africa, where there is historic evidence of a choline-poor diet, and the other in the United States, with a comparatively choline-rich diet. We used 2 independent methods, and confirmation of our hypothesis was sought via a comparison with SNP data from the Maasai, an East African population with a genetic background similar to that of Gambians but with a traditional diet that is higher in choline. Our results show that frequencies of SNPs known to increase dependence on dietary choline are significantly reduced in the low-choline setting of The Gambia. Our findings suggest that adequate intake levels of choline may have to be reevaluated in different ethnic groups and highlight a possible approach for identifying novel functional SNPs under the influence of dietary selective pressure

Associations of Dietary Intake with the Intestinal Microbiota and Short-Chain Fatty Acids Among Young Adults with Type 1 Diabetes and Overweight or Obesity

Background: Diet, a key component of type 1 diabetes (T1D) management, modulates the intestinal microbiota and its metabolically active byproducts—including SCFA—through fermentation of dietary carbohydrates such as fiber. However, the diet–microbiome relationship remains largely unexplored in longstanding T1D. Objectives: We evaluated whether increased carbohydrate intake, including fiber, is associated with increased SCFA-producing gut microbes, SCFA, and intestinal microbial diversity among young adults with longstanding T1D and overweight or obesity. Methods: Young adult men and women with T1D for ≥1 y, aged 19–30 y, and BMI of 27.0–39.9 kg/m2 at baseline provided stool samples at baseline and 3, 6, and 9 mo of a randomized dietary weight loss trial. Diet was assessed by 1–2 24-h recalls. The abundance of SCFA-producing microbes was measured using 16S rRNA gene sequencing. GC-MS measured fecal SCFA (acetate, butyrate, propionate, and total) concentrations. Adjusted and Bonferroni-corrected generalized estimating equations modeled associations of dietary fiber (total, soluble, and pectins) and carbohydrate (available carbohydrate, and fructose) with microbiome-related outcomes. Primary analyses were restricted to data collected before COVID-19 interruptions. Results: Fiber (total and soluble) and carbohydrates (available and fructose) were positively associated with total SCFA and acetate concentrations (n = 40 participants, 52 visits). Each 10 g/d of total and soluble fiber intake was associated with an additional 8.8 μmol/g (95% CI: 4.5, 12.8 μmol/g; P = 0.006) and 24.0 μmol/g (95% CI: 12.9, 35.1 μmol/g; P = 0.003) of fecal acetate, respectively. Available carbohydrate intake was positively associated with SCFA producers Roseburia and Ruminococcus gnavus. All diet variables except pectin were inversely associated with normalized abundance of Bacteroides and Alistipes. Fructose was inversely associated with Akkermansia abundance. Conclusions: In young adults with longstanding T1D, fiber and carbohydrate intake were associated positively with fecal SCFA but had variable associations with SCFA-producing gut microbes. Controlled feeding studies should determine whether gut microbes and SCFA can be directly manipulated in T1D

Genetic signatures in choline and 1-carbon metabolism are associated with the severity of hepatic steatosis

Choline metabolism is important for very low-density lipoprotein secretion, making this nutritional pathway an important contributor to hepatic lipid balance. The purpose of this study was to assess whether the cumulative effects of multiple single nucleotide polymorphisms (SNPs) across genes of choline/ 1-carbon metabolism and functionally related pathways increase susceptibility to developing hepatic steatosis. In biopsy-characterized cases of nonalcoholic fatty liver disease and controls, we assessed 260 SNPs across 21 genes in choline/1-carbon metabolism. When SNPs were examined individually, using logistic regression, we only identified a single SNP (PNPLA3 rs738409) that was significantly associated with severity of hepatic steatosis after adjusting for confounders and multiple comparisons (P=0.02). However, when groupings of SNPs in similar metabolic pathways were defined using unsupervised hierarchical clustering, we identified groups of subjects with shared SNP signatures that were significantly correlated with steatosis burden (P=0.0002). The lowest and highest steatosis clusters could also be differentiated by ethnicity. However, unique SNP patterns defined steatosis burden irrespective of ethnicity. Our results suggest that analysis of SNP patterns in genes of choline/1-carbon metabolism may be useful for prediction of severity of steatosis in specific subsets of people, and the metabolic inefficiencies caused by these SNPs should be examined further

Associations of disordered eating with the intestinal microbiota and short-chain fatty acids among young adults with type 1 diabetes

Background and aims: Disordered eating (DE) in type 1 diabetes (T1D) includes insulin restriction for weight loss with serious complications. Gut microbiota-derived short chain fatty acids (SCFA) may benefit host metabolism but are reduced in T1D. We evaluated the hypothesis that DE and insulin restriction were associated with reduced SCFA-producing gut microbes, SCFA, and intestinal microbial diversity in adults with T1D. Methods and results: We collected stool samples at four timepoints in a hypothesis-generating gut microbiome pilot study ancillary to a weight management pilot in young adults with T1D. 16S ribosomal RNA gene sequencing measured the normalized abundance of SCFA-producing intestinal microbes. Gas-chromatography mass-spectrometry measured SCFA (total, acetate, butyrate, and propionate). The Diabetes Eating Problem Survey—Revised (DEPS-R) assessed DE and insulin restriction. Covariate-adjusted and Bonferroni-corrected generalized estimating equations modeled the associations. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 data. Data were available for 45 participants at 109 visits, which included 42 participants at 65 visits pre-COVID-19. Participants reported restricting insulin “At least sometimes” at 53.3% of visits. Pre-COVID-19, each 5-point DEPS-R increase was associated with a −0.34 (95% CI -0.56, −0.13, p = 0.07) lower normalized abundance of genus Anaerostipes; and the normalized abundance of Lachnospira genus was −0.94 (95% CI -1.5, −0.42), p = 0.02 lower when insulin restriction was reported “At least sometimes” compared to “Rarely or Never”. Conclusion: DE and insulin restriction were associated with a reduced abundance of SCFA-producing gut microbes pre-COVID-19. Additional studies are needed to confirm these associations to inform microbiota-based therapies in T1D

Navigating institutional pressure in state-socialist and democratic regimes: The case of movement brontosaurus

Using the case of Movement Brontosaurus, a Czech organization founded in state socialist times, this article investigates how civic associations and nongovernmental organizations seeking to promote alternatives to the status quo respond to institutional pressures in different political and social contexts. The case shows that under state socialism, Brontosaurus appeared to conform to state mandates and societal expectations. However, its formal structure was decoupled from many activities to obscure its oppositional intent.After the transition to democracy, the organization was only able to maintain its place in society after it aligned its structure and practices with each other and openly expressed its alternative agenda. The findings demonstrate how social change and alternative lifestyle organizations vary their responses to institutional pressure in ways that enable them to realize their values and pursue their missions while accounting for the political and social contexts in which they are embedded

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Diabetes mellitus: pathophysiological changes and therap