Meta-analysis has shown a modest improvement in first-year growth response to recombinant human GH (r-hGH) for carriers of the exon 3-deleted GH receptor (GHRd3) polymorphism but with significant ...interstudy variability. The associations between GHRd3 and growth response to r-hGH over 3 years in relation to severity of GH deficiency (GHD) were investigated in patients from 14 countries. Treatment-naïve pre-pubertal children with GHD were enrolled from the PREDICT studies (NCT00256126 and NCT00699855), categorized by peak GH level (peak GH) during provocation test: ≤4 μg/l (severe GHD; n=45) and >4 to <10 μg/l mild GHD; n=49) and genotyped for the GHRd3 polymorphism (full length (fl/fl, fl/d3, d3/d3). Gene expression (GE) profiles were characterized at baseline. Changes in growth (height (cm) and SDS) over 3 years were measured. There was a dichotomous influence of GHRd3 polymorphism on response to r-hGH, dependent on peak GH level. GH peak level (higher vs lower) and GHRd3 (fl/fl vs d3 carriers) combined status was associated with height change over 3 years (P<0.05). GHRd3 carriers with lower peak GH had lower growth than subjects with fl/fl (median difference after 3 years -3.3 cm; -0.3 SDS). Conversely, GHRd3 carriers with higher peak GH had better growth (+2.7 cm; +0.2 SDS). Similar patterns were observed for GH-dependent biomarkers. GE profiles were significantly different between the groups, indicating that the interaction between GH status and GHRd3 carriage can be identified at a transcriptomic level. This study demonstrates that responses to r-hGH depend on the interaction between GHD severity and GHRd3 carriage.
The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing ...heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval 9.6×10(-5)-3.1×10(-4)); accounts overall for 0.5% 0.19%-0.82% of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 9.9-60.6); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) 1.8-10.3 in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.
Salivary α- amylase (AMY1) is responsible for the breakdown of starch into oligosaccharides, tri and di-saccharides giving a start to the starch digestion in the oral cavity on food consumption. ...Several studies recently reported contradicting results regarding the link between AMY1 copy numbers (CNs) and obesity and type 2 diabetes.
Objective: We investigated whether CN in the AMY1 gene was associated with differential anthropometrics and glycaemic outcomes in obese individuals who underwent a dietary plan varying in macronutrient intake, as a part of weight loss and weight maintenance program. We also investigated whether there existed an interaction between nutrient intakes and AMY1 CNs and if AMY1 CNs have influence on body weight, body composition and glycemic trajectories during dietary interventions.
Using the Paralogue Ratio Test, we accurately measured the AMY1 CNs in 761 obese individuals from the Diogenes study. Subjects underwent first an 8-week low-caloric diet (LCD, at 800 kcal/d) and those achieving >8% weight loss were then randomized to a 6-month weight maintenance dietary (WMD) intervention. The association between AMY1 CNs and weight- and glycemic- parameters was tested at baseline and following each intervention phase (LCD, WMD) with the use of linear mixed effect models adjusting for gender, age, center and total energy intake.
At baseline, a modest association between AMY1 CN and BMI (P = 0.04) was observed. AMY1 CN was not associated with baseline glycemic variables. Additionally, AMY1 CN was not associated with anthropometric or glycemic-outcomes following either LCD or WMD. Interaction analyses between AMY1 CN and nutrient intake did not reveal significant association with any clinical parameters (at baseline and following LCD or WMD) or when testing gene x WMD interactions during the WMD phase
In the absence of association with weight trajectories or glycemic improvements, the AMY1 CN cannot be considered as an important biomarker for response to a clinical weight loss and weight maintenance programs in overweight/obese subjects.
European Commission, Food Quality and Safety Priority of the Sixth Framework Program (FP6-2005-513946), Nestlé Institute of Health Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The extracellular matrix (ECM) of adipocytes is important for body weight regulation. Here, we investigated whether genetic variation in ECM-related genes is associated with weight regain among ...participants of the European DiOGenes study. Overweight and obese subjects (n = 469, 310 females, 159 males) were on an 8-week low-calorie diet with a 6-month follow-up. Body weight was measured before and after the diet, and after follow-up. Weight maintenance scores (WMS, regained weight as percentage of lost weight) were calculated based on the weight data. Genotype data were retrieved for 2903 SNPs corresponding to 124 ECM-related genes. Regression analyses provided us with six significant SNPs associated with the WMS in males: 3 SNPs in the POSTN gene and a SNP in the LAMB1, COL23A1, and FBLN5 genes. For females, 1 SNP was found in the FN1 gene. The risk of weight regain was increased by: the C/C genotype for POSTN in a co-dominant model (OR 8.25, 95 % CI 2.85–23.88) and the T/C–C/C genotype in a dominant model (OR 4.88, 95 % CI 2.35–10.16); the A/A genotype for LAMB1 both in a co-dominant model (OR 18.43, 95 % CI 2.35–144.63) and in a recessive model (OR 16.36, 95 % CI 2.14–124.9); the G/A genotype for COL23A1 in a co-dominant model (OR 3.94, 95 % CI 1.28–12.10), or the A-allele in a dominant model (OR 2.86, 95 % CI 1.10–7.49); the A/A genotype for FBLN5 in a co-dominant model (OR 13.00, 95 % CI 1.61–104.81); and the A/A genotype for FN1 in a recessive model (OR 2.81, 95 % CI 1.40–5.63). Concluding, variants of ECM genes are associated with weight regain after weight loss in a sex-specific manner.
Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of ...recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%. The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA. In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.
Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of ...recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%. The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA. In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.
We present a tool designed for visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies. This software provides an integrated framework to ...facilitate the interpretation of SNP association studies in genomic context. Gene annotations can be retrieved from Ensembl, linkage disequilibrium data downloaded from HapMap and custom data imported in BED or WIG format. AssociationViewer integrates functionalities that enable the aggregation or intersection of data tracks. It implements an efficient cache system and allows the display of several, very large-scale genomic datasets. Availability: The Java code for AssociationViewer is distributed under the GNU General Public Licence and has been tested on Microsoft Windows XP, MacOSX and GNU/Linux operating systems. It is available from the SourceForge repository. This also includes Java webstart, documentation and example datafiles. Contact: brian.stevenson@licr.org Supplementary information: Supplementary data are available at http://sourceforge.net/projects/associationview/ online.
Motivation: Current clinical and biological studies apply different biotechnologies and subsequently combine the resulting -omics data to test biological hypotheses. The plethora of -omics data and ...their combination generates a large number of hypotheses and apparently increases the study power. Contrary to these expectations, the wealth of -omics data may even reduce the statistical power of a study because of a large correction factor for multiple testing. Typically, this loss of power in analyzing -omics data are caused by an increased false detection rate (FDR) in measurements, like falsely detected DNA copy number changes, or falsely identified differentially expressed genes. The false detections are random and, therefore, not related to the tested conditions. Thus, a high FDR considerably decreases the discovery power of studies, especially if different -omics data are involved.
Results: On a HapMap data set, where known CNVs have to be re-detected, I/NI call filtering was much more efficient than variance-based filtering. In particular, the I/NI call filter outperforms variance-based filters on data with rare events like the CNVs in the HapMap data set. We assessed the efficiency of the I/NI call filter in reducing the FDR on two different cancer cell lines where it reduced the FDR 18- to 22-fold.
Materials and Methods: A mitigation strategy for too high FDRs is to filter out putative false detections. We suggest using probabilistic latent variable models to identify putative false detections which may be found via such models by high estimated noise or by model-based measurement inconsistencies across samples. To select such a model, a Bayesian approach starts with the maximum a priori model that assumes no detection and selects the maximum a posteriori model. Hence detection results in a deviation of the maximal posterior from the maximal prior model measured by the information gain obtained by the data. If this information gain exceeds a threshold then the selected model obtains an Informative/Non-Informative (I/NI) call that indicates a detection. I/NI call filtering has been successfully applied in different projects, but it has so far not been shown that correction for multiple testing after I/NI call filtering still controls the type-I error rate. We prove this important property of the I/NI call and show that it is independent of commonly used test statistics for null hypotheses. We apply the I/NI call to transcriptomics (gene expression), where the prior model corresponds to a constant gene expression level across compared samples, and to genomics, analyzing copy number variation (CNV) data, where the prior model corresponds to a constant DNA copy number of 2 across compared samples.
Adipose tissue (AT) transcriptome studies provide holistic pictures of adaptation to weight and related bioclinical settings changes. Objective To implement AT gene expression profiling and ...investigate the link between changes in bioclinical parameters and AT gene expression during 3 steps of a 2-phase dietary intervention (DI). Methods AT transcriptome profiling was obtained from sequencing 1051 samples, corresponding to 556 distinct individuals enrolled in a weight loss intervention (8-week low-calorie diet (LCD) at 800 kcal/day) followed with a 6-month ad libitum randomized DI. Transcriptome profiles obtained with QuantSeq sequencing were benchmarked against Illumina RNAseq. Reverse transcription quantitative polymerase chain reaction was used to further confirm associations. Cell specificity was assessed using freshly isolated cells and THP-1 cell line. Results During LCD, 5 modules were found, of which 3 included at least 1 bioclinical variable. Change in body mass index (BMI) connected with changes in mRNA level of genes with inflammatory response signature. In this module, change in BMI was negatively associated with changes in expression of genes encoding secreted protein (GDF15, CCL3, and SPP1). Through all phases of the DI, change in GDF15 was connected to changes in SPP1, CCL3, LIPA and CD68. Further characterization showed that these genes were specific to macrophages (with LIPA, CD68 and GDF15 expressed in anti-inflammatory macrophages) and GDF15 also expressed in preadipocytes. Conclusion Network analyses identified a novel AT feature with GDF15 upregulated with calorie restriction induced weight loss, concomitantly to macrophage markers. In AT, GDF15 was expressed in preadipocytes and macrophages where it was a hallmark of anti-inflammatory cells.
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