An increase of plasma kynurenine concentrations, potentially bioactive metabolites of tryptophan, was found in subjects with obesity, resulting from low-grade inflammation of the white adipose ...tissue. Bariatric surgery decreases low-grade inflammation associated with obesity and improves glucose control.
Our goal was to determine the concentrations of all kynurenine metabolites after bariatric surgery and whether they were correlated with glucose control improvement.
Kynurenine metabolite concentrations, analysed by liquid or gas chromatography coupled with tandem mass spectrometry, circulating inflammatory markers, metabolic traits, and BMI were measured before and one year after bariatric surgery in 44 normoglycemic and 47 diabetic women with obesity. Associations between changes in kynurenine metabolites concentrations and in glucose control and metabolic traits were analysed between baseline and twelve months after surgery.
Tryptophan and kynurenine metabolite concentrations were significantly decreased one year after bariatric surgery and were correlated with the decrease of the usCRP in both groups. Among all the kynurenine metabolites evaluated, only quinolinic acid and xanthurenic acid were significantly associated with glucose control improvement. The one year delta of quinolinic acid concentrations was negatively associated with the delta of fasting glucose (p = 0.019) and HbA1c (p = 0.014), whereas the delta of xanthurenic acid was positively associated with the delta of insulin sensitivity index (p = 0.0018).
Bariatric surgery has induced a global down-regulation of kynurenine metabolites, associated with weight loss. Our results suggest that, since kynurenine monoxygenase diverts the kynurenine pathway toward the synthesis of xanthurenic acid, its inhibition may also contribute to glucose homeostasis.
Aims/hypothesis
Genome-wide association studies have firmly established 65 independent European-derived loci associated with type 2 diabetes and 36 loci contributing to variations in fasting plasma ...glucose (FPG). Using individual data from the Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) prospective study, we evaluated the contribution of three genetic risk scores (GRS) to variations in metabolic traits, and to the incidence and prevalence of impaired fasting glycaemia (IFG) and type 2 diabetes.
Methods
Three GRS (GRS-1, 65 type 2 diabetes-associated single nucleotide polymorphisms SNPs; GRS-2, GRS-1 combined with 24 FPG-raising SNPs; and GRS-3, FPG-raising SNPs alone) were analysed in 4,075 DESIR study participants. GRS-mediated effects on longitudinal variations in quantitative traits were assessed in 3,927 nondiabetic individuals using multivariate linear mixed models, and on the incidence and prevalence of hyperglycaemia at 9 years using Cox and logistic regression models. The contribution of each GRS to risk prediction was evaluated using the C-statistic and net reclassification improvement (NRI) analysis.
Results
The two most inclusive GRS were significantly associated with increased FPG (β = 0.0011 mmol/l per year per risk allele,
p
GRS-1
= 8.2 × 10
−5
and
p
GRS-2
= 6.0 × 10
−6
), increased incidence of IFG and type 2 diabetes (per allele: HR
GRS-1
1.03,
p
= 4.3 × 10
−9
and HR
GRS-2
1.04,
p
= 1.0 × 10
−16
), and the 9 year prevalence (OR
GRS-1
1.13 95% CI 1.10, 1.17,
p
= 1.9 × 10
−14
for type 2 diabetes only; OR
GRS-2
1.07 95% CI 1.05, 1.08,
p
= 7.8 × 10
−25
, for IFG and type 2 diabetes). No significant interaction was found between GRS-1 or GRS-2 and potential confounding factors. Each GRS yielded a modest, but significant, improvement in overall reclassification rates (NRI
GRS-1
17.3%,
p
= 6.6 × 10
−7
; NRI
GRS-2
17.6%,
p
= 4.2 × 10
−7
; NRI
GRS-3
13.1%,
p
= 1.7 × 10
−4
).
Conclusions/interpretation
Polygenic scores based on combined genetic information from type 2 diabetes risk and FPG variation contribute to discriminating middle-aged individuals at risk of developing type 2 diabetes in a general population.
Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. ...These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach.
We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity.
We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation.
These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.
Null mutations in the PCSK1 gene, encoding the proprotein convertase 1/3 (PC1/3), cause recessive monogenic early onset obesity. Frequent coding variants that modestly impair PC1/3 function mildly ...increase the risk for common obesity. The aim of this study was to determine the contribution of rare functional PCSK1 mutations to obesity. PCSK1 exons were sequenced in 845 nonconsanguineous extremely obese Europeans. Eight novel nonsynonymous PCSK1 mutations were identified, all heterozygous. Seven mutations had a deleterious effect on either the maturation or the enzymatic activity of PC1/3 in cell lines. Of interest, five of these novel mutations, one of the previously described frequent variants (N221D), and the mutation found in an obese mouse model (N222D), affect residues at or near the structural calcium binding site Ca-1. The prevalence of the newly identified mutations was assessed in 6,233 obese and 6,274 lean European adults and children, which showed that carriers of any of these mutations causing partial PCSK1 deficiency had an 8.7-fold higher risk to be obese than wild-type carriers. These results provide the first evidence of an increased risk of obesity in heterozygous carriers of mutations in the PCSK1 gene. Furthermore, mutations causing partial PCSK1 deficiency are present in 0.83% of extreme obesity phenotypes.
Context:
Young-onset obesity is strongly associated with the early development of type 2 diabetes (T2D). Genetic risk scores (GRSs) related to T2D might help predicting the early impairment of ...glucose homeostasis in obese youths.
Objective:
Our objective was to investigate the contributions of four GRSs (associated with: T2D GRS-T2D, beta-cell function GRS-β, insulin resistance GRS-IR, and body mass index) to the variation of traits derived from oral glucose tolerance test (OGTT) in obese and normal-weight children and young adults.
Design:
This was a cross-sectional association study.
Patients:
A total of 1076 obese children/adolescents (age = 11.4 ± 2.8 years) and 1265 normal-weight young volunteers (age = 21.1 ± 4.4 years) of European ancestry were recruited from pediatric obesity clinics and general population, respectively.
Intervention:
Standard OGTT was the intervention in this study.
Main Outcome Measures:
Associations between GRSs and OGTT-derived traits including fasting glucose and insulin, insulinogenic index, insulin sensitivity index, disposition index (DI) and associations between GRSs and pre-diabetic conditions were measured.
Results:
GRS-β significantly associated with fasting glucose (β = 0.019; P = 3.5 × 10−4) and DI (β = −0.031; P = 8.9 × 10−4, last quartile 18% lower than first) in obese children, and nominally associated with fasting glucose (β = 0.009; P = 0.017) and DI (β = −0.030; P = 1.1 × 10−3, last quartile 11% lower than first) in normal-weight youths. GRS-T2D showed weaker contribution to fasting glucose and DI compared to GRS-β, in both obese and normal-weight youths. GRS associated with insulin resistance and GRS associated with body mass index did not associate with any traits. None of the GRSs associated with prediabetes, which affected only 4% of participants overall.
Conclusion:
Single nucleotide polymorphisms identified by genome-wide association studies to influence beta-cell function were associated with fasting glucose and indices of insulin secretion in youths, especially in obese children.
We aimed to investigate the contributions of four GRSs related to diabetes, to the variation of traits derived from oral glucose tolerance test in obese and normal-weight children and young adults.
Abstract
Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in ∼250000 European participants have led to the discovery of ∼700 and ∼100 nearly independent single ...nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N ∼700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P < 1 × 10−8), including 1185 height-associated SNPs and 751 BMI-associated SNPs located within loci not previously identified by these two GWAS. The near-independent genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼6.0% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were ∼0.44 and ∼0.22, respectively. From analyses of integrating GWAS and expression quantitative trait loci (eQTL) data by summary-data-based Mendelian randomization, we identified an enrichment of eQTLs among lead height and BMI signals, prioritizing 610 and 138 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by the discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow-up studies.
The original version of this Article contained an error in the spelling of the author Julia Sidorenko, which was incorrectly given as Julia Sirodenko. This has now been corrected in both the PDF and ...HTML versions of the Article. Further, the sixth sentence of the second paragraph of the Correspondence and the legend to Fig. 1 incorrectly omitted citation of work by Heilmann-Helmbach, S. et al. This has now been corrected in both the PDF and HTML versions of the Article.
Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple ...genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS) to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS). Despite the relatively small size of GHS (n = 3,175), when compared with the largest published meta-GWAS (n > 100,000), GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify associated variants. This provides a powerful tool for the analysis of diverse genomic features, for instance including gene expression and exome sequencing data, where complex dependencies are present in the predictor space.
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