Identification of ALK in Thinness.

There is considerable inter-individual variability in susceptibility to weight gain despite an equally obesogenic environment in large parts of the world. Whereas many studies have focused on identifying the genetic susceptibility to obesity, we performed a GWAS on metabolically healthy thin individuals (lowest 6th percentile of the population-wide BMI spectrum) in a uniquely phenotyped Estonian cohort. We discovered anaplastic lymphoma kinase (ALK) as a candidate thinness gene. In Drosophila, RNAi mediated knockdown of Alk led to decreased triglyceride levels. In mice, genetic deletion of Alk resulted in thin animals with marked resistance to diet- and leptin-mutation-induced obesity. Mechanistically, we found that ALK expression in hypothalamic neurons controls energy expenditure via sympathetic control of adipose tissue lipolysis. Our genetic and mechanistic experiments identify ALK as a thinness gene, which is involved in the resistance to weight gain.

A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma.

Molecular quantitative trait locus (QTL) analyses are increasingly popular to explore the genetic architecture of complex traits, but existing studies do not leverage shared regulatory patterns and suffer from a large multiplicity burden, which hampers the detection of weak signals such as trans associations. Here, we present a fully multivariate proteomic QTL (pQTL) analysis performed with our recently proposed Bayesian method LOCUS on data from two clinical cohorts, with plasma protein levels quantified by mass-spectrometry and aptamer-based assays. Our two-stage study identifies 136 pQTL associations in the first cohort, of which >80% replicate in the second independent cohort and have significant enrichment with functional genomic elements and disease risk loci. Moreover, 78% of the pQTLs whose protein abundance was quantified by both proteomic techniques are confirmed across assays. Our thorough comparisons with standard univariate QTL mapping on (1) these data and (2) synthetic data emulating the real data show how LOCUS borrows strength across correlated protein levels and markers on a genome-wide scale to effectively increase statistical power. Notably, 15% of the pQTLs uncovered by LOCUS would be missed by the univariate approach, including several trans and pleiotropic hits with successful independent validation. Finally, the analysis of extensive clinical data from the two cohorts indicates that the genetically-driven proteins identified by LOCUS are enriched in associations with low-grade inflammation, insulin resistance and dyslipidemia and might therefore act as endophenotypes for metabolic diseases. While considerations on the clinical role of the pQTLs are beyond the scope of our work, these findings generate useful hypotheses to be explored in future research; all results are accessible online from our searchable database. Thanks to its efficient variational Bayes implementation, LOCUS can analyze jointly thousands of traits and millions of markers. Its applicability goes beyond pQTL studies, opening new perspectives for large-scale genome-wide association and QTL analyses. Diet, Obesity and Genes (DiOGenes) trial registration number: NCT00390637.

Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance.

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.

Insulin Resistance during normal child growth and development is associated with a distinct blood metabolic phenotype (Earlybird 72).

BACKGROUND: While insulin resistance (IR) is associated with specific metabolite signatures in adults, there have been few truly longitudinal studies in healthy children, either to confirm which abnormalities are present, or to determine whether they precede or result from IR. Therefore, we investigated the association of serum metabolites with IR in childhood in the Earlybird cohort. METHODS: The Earlybird cohort is a well-characterized cohort of healthy children with annual measurements from age 5 to 16 years. For the first time, longitudinal association analyses between individual serum metabolites and homeostatic model assessment (HOMA) of insulin resistance (HOMA-IR) have been performed taking into account the effects of age, growth, puberty, adiposity, and physical activity. RESULTS: IR was higher in girls than in boys and was associated with increasing body mass index (BMI). In longitudinal analysis IR was associated with reduced concentrations of branched-chain amino acids (BCAA), 2-ketobutyrate, citrate and 3-hydroxybutyrate, and higher concentrations of lactate and alanine. These findings demonstrate the widespread biochemical consequences of IR for intermediary metabolism, ketogenesis, and pyruvate oxidation during normal child growth and development. CONCLUSIONS: Longitudinal analysis can differentiate metabolite signatures that precede or follow the development of greater levels of IR. In healthy normal weight children, higher levels of IR are associated with reduced levels of BCAA, ketogenesis, and fuel oxidation. In contrast, elevated lactate concentrations preceded the rise in IR. These changes reveal the metabolite signature of insulin action during normal growth, and they contrast with previous findings in obese children and adults that represent the consequences of IR and obesity.

Efficient inference for genetic association studies with multiple outcomes.

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson and others (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes.

Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

Circulating lipid levels and risk of coronary artery disease in a large group of patients undergoing coronary angiography.

A main underlying pathology of coronary artery disease is the deposition of cholesterol in the arteries supplying blood to the heart that leads to stenosis and myocardial infarction. We tested if dyslipidemia is a risk factor for coronary artery disease in the Lebanese population, and studied the role of the total cholesterol/HDL cholesterol (TC/HDL-C) ratio as a biological marker of coronary artery disease. We recruited 6,180 Lebanese patients undergoing cardiac catheterization. We conducted a cross-sectional association study between TC/HDL-C ratio and the number and type of vessels occluded in catheterized patients by controlling for confounding effects. The TC/HDL-C ratio ≥4 significantly predicts ≥50 % stenosis in all vessels individually with the odds ratio (OR) ranging from 1.22 to 1.92. The OR increased with increasing number of ≥50 % stenotic vessels (1.39 for 2 vessels and 1.64 for 3-4 vessels), as did risk due to diabetes, CAD family history, gender, and age. The younger than average age of onset subgroup shows a pronounced increase in risk for occlusion of the left main coronary artery due to TC/HDL-C ≥4 (OR 3.26). In conclusion, low levels of HDL-cholesterol and high levels TC/HDL-C ratio are strong biological markers of disease occurrence and severity in the Lebanese population.

Determinants of human adipose tissue gene expression: impact of diet, sex, metabolic status, and cis genetic regulation.

Weight control diets favorably affect parameters of the metabolic syndrome and delay the onset of diabetic complications. The adaptations occurring in adipose tissue (AT) are likely to have a profound impact on the whole body response as AT is a key target of dietary intervention. Identification of environmental and individual factors controlling AT adaptation is therefore essential. Here, expression of 271 transcripts, selected for regulation according to obesity and weight changes, was determined in 515 individuals before, after 8-week low-calorie diet-induced weight loss, and after 26-week ad libitum weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently controlled AT gene expression. These analyses help understanding the relative importance of environmental and individual factors that control the expression of human AT genes and therefore may foster strategies aimed at improving AT function in metabolic diseases.

TFAP2B -dietary protein and glycemic index interactions and weight maintenance after weight loss in the DiOGenes trial.

BACKGROUND: TFAP2B rs987237 is associated with obesity and has shown interaction with the dietary fat-to-carbohydrate ratio, which has an effect on weight loss. We investigated interactions between rs987237 and protein-to-carbohydrate ratio or glycemic index (GI) in relation to weight maintenance after weight loss. METHODS: This study included 742 obese individuals from 8 European countries who participated in the Diet, Obesity, and Genes (DiOGenes) trial, lost ≥ 8% of their initial body weight during an 8-week low-calorie diet and were randomized to one of 5 ad libitum diets with a fixed energy percentage from fat: either low-protein/low-GI, low-protein/high-GI, high-protein/low-GI, or high-protein/high-GI diets, or a control diet for a 6-month weight maintenance period. Using linear regression analyses and additive genetic models, we investigated main and dietary interaction effects of TFAP2B rs987237 in relation to weight maintenance. RESULTS: In total, 468 completers of the trial were genotyped for rs987237. High-protein diets were beneficial for weight maintenance in the AA genotype group (67% of participants), but in the AG and GG groups no differences were observed for low- or high-protein diets. On the high-protein diet, carriers of the obesity risk allele (G allele) regained 1.84 kg (95% CI: 0.02; 3.67, p = 0.047) more body weight per risk allele than individuals on a low-protein diet. There was no interaction effect between rs987237 and GI on weight maintenance. CONCLUSION: TFAP2B rs987237 and dietary protein/carbohydrate interacted to modify weight maintenance. Considering the carbohydrate proportion of the diet, the interaction was different from the previously reported rs987237-fat-to-carbohydrate ratio interaction for weight loss. Thus, TFAP2B-macronutrient interactions might diverge depending on the nutritional state.

Application of an online-biomass sensor in an optical multisensory platform prototype for growth monitoring of biotechnical relevant microorganism and cell lines in single-use shake flasks.

In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations.

Influence of SNPs in nutrient-sensitive candidate genes and gene-diet interactions on blood lipids: the DiOGenes study.

Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene-diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile after weight loss and in response to a given diet, among overweight European adults participating in the Diet Obesity and Genes study. By multiple linear regressions, 240 SNPs in twenty-four candidate genes were investigated for SNP main and SNP-diet interaction effects on total cholesterol, LDL-cholesterol, HDL-cholesterol and TAG after an 8-week low-energy diet (only main effect) ,and a 6-month ad libitum weight maintenance diet, with different contents of dietary protein or glycaemic index. After adjusting for multiple testing, a SNP-dietary protein interaction effect on TAG was identified for lipin 1 (LPIN1) rs4315495, with a decrease in TAG of 20.26 mmol/l per A-allele/protein unit (95% CI 20.38, 20.14, P=0.000043). In conclusion, we investigated SNP-diet interactions for blood lipid profiles for 240 SNPs in twenty-four candidate genes, selected for their involvement in lipid metabolism pathways, and identified one significant interaction between LPIN1 rs4315495 and dietary protein for TAG concentration.

Adipose tissue angiogenesis genes are down-regulated by grape polyphenols supplementation during a human overfeeding trial.

The adaptive response to overfeeding is associated with profound modifications of gene expression in adipose tissue to support lipid storage and weight gain. The objective of this study was to assess in healthy lean men whether a supplementation with polyphenols could interact with these molecular adaptations. Abdominal subcutaneous adipose tissue biopsies were sampled from 42 subjects participating to an overfeeding protocol providing an excess of 50% of their total energy expenditure for 31 days, and who were supplemented with 2 g/day of grape polyphenols or a placebo. Gene expression profiling was performed by RNA sequencing. Overfeeding led to a modification of the expression of 163 and 352 genes in the placebo and polyphenol groups, respectively. The GO functions of these genes were mostly involved in lipid metabolism, followed by genes involved in adipose tissue remodeling and expansion. In response to overfeeding, 812 genes were differentially regulated between groups. Among them, a set of 41 genes were related to angiogenesis and were down-regulated in the polyphenol group. Immunohistochemistry targeting PECAM1, as endothelial cell marker, confirmed reduced angiogenesis in this group. Finally, quercetin and isorhamnetin, two polyphenol species enriched in the plasma of the volunteers submitted to the polyphenols, were found to inhibit human umbilical vein endothelial cells migration in vitro. Polyphenol supplementation do not prevent the regulation of genes related to lipid metabolism in human adipose tissue during overfeeding, but impact the angiogenesis pathways. This may potentially contribute to a protection against adipose tissue expansion during dynamic phase of weight gain.

The EvA study: aims and strategy.

The EvA study is a European Union-funded project under the Seventh Framework Programme (FP7), which aims at defining new markers for chronic obstructive pulmonary disease (COPD) and its subtypes. The acronym is derived from emphysema versus airway disease, indicating that the project targets these two main phenotypes of the disease. The EvA study is based on the concept that emphysema and airway disease are governed by different pathophysiological processes, are driven by different genes and have differential gene expression in the lung. To define these genes, patients and non-COPD controls are recruited for clinical examination, lung function analysis and computed tomography (CT) of the lung. CT scans are used to define the phenotypes based on lung density and airway wall thickness. This is followed by bronchoscopy in order to obtain samples from the airways and the alveoli. These tissue samples, along with blood samples, are then subjected to genome-wide expression and association analysis and markers linked to the phenotypes are identified. The population of the EvA study is different from other COPD study populations, since patients with current oral glucocorticoids, antibiotics and exacerbations or current smokers are excluded, such that the signals detected in the molecular analysis are due to the distinct inflammatory process of emphysema and airway disease in COPD.

Proteomics reveals unique plasma signatures in constitutional thinness.

PURPOSE: Studying the plasma proteome of control versus constitutionally thin (CT) individuals, exposed to overfeeding, may give insights into weight-gain management, providing relevant information to the clinical entity of weight-gain resistant CT, and discovering new markers for the condition. EXPERIMENTAL DESIGN: Untargeted protein relative quantification of 63 CT and normal-weight individuals was obtained in blood plasma at baseline, during and after an overfeeding challenge using mass spectrometry-based proteomics. RESULTS: The plasma proteome of CT subjects presented limited specificity with respect to controls at baseline. Yet, CT showed lower levels of inflammatory C-reactive protein and larger levels of protective insulin-like growth factor-binding protein 2. Differences were more marked during and after overfeeding. CT plasma proteome showed larger magnitude and significance in response, suggesting enhanced "resilience" and more rapid adaptation to changes. Four proteins behaved similarly between CT and controls, while five were regulated in opposite fashion. Ten proteins were differential during overfeeding in CT only (including increased fatty acid-binding protein and glyceraldehyde-3-phosphate dehydrogenase, and decreased apolipoprotein C-II and transferrin receptor protein 1). CONCLUSIONS AND CLINICAL RELEVANCE: This first proteomic profiling of a CT cohort reveals different plasma proteomes between CT subjects and controls in a longitudinal clinical trial. Our molecular observations further support that the resistance to weight gain in CT subjects appears predominantly biological. CLINICALTRIALS: gov Identifier: NCT02004821.

New Insights on Bone Tissue and Structural Muscle-Bone Unit in Constitutional Thinness.

While few studies pointed out low bone mineral densities in constitutionally thin women, little is known about potential explanations. The objective was to further explore bone architecture in both women and men with constitutional thinness to investigate their mechanical muscle-bone coupling (or uncoupling). Thirty constitutionally thin people and 31 normal weight controls participated in the study. Body composition, hip structural analysis, and trabecular bone score were assessed by dual-energy X-ray absorptiometry, bone architecture using high-resolution peripheral quantitative computed tomography, and muscle explorations through histological staining on muscle biopsies. Thirty-two out of the 48 indexes relative to density, geometry, texture, and architecture of bones were found significantly lower (p < 0.05) in constitutionally thin individuals compared with controls. This observation was particularly pronounced in constitutionally thin men. Bone microarchitecture was more altered in weight-supporting bone (tibia) than in non-weight-supporting (radius) bone, which might refer to a normal physiological adaptation (Frost's mechanostat theory). Yet, the heat-maps of correlations analyses showed many alterations of body weight or muscle associations with bone parameters in constitutionally thin individuals contrary to controls. Present results might support the idea of intrinsic disturbances of bone cells independently to the small muscle structure, particularly in men.

Network Analyses Reveal Negative Link Between Changes in Adipose Tissue GDF15 and BMI During Dietary-induced Weight Loss.

CONTEXT: 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.

Grape polyphenols decrease circulating branched chain amino acids in overfed adults.

Introduction and aims: Dietary polyphenols have long been associated with health benefits, including the prevention of obesity and related chronic diseases. Overfeeding was shown to rapidly induce weight gain and fat mass, associated with mild insulin resistance in humans, and thus represents a suitable model of the metabolic complications resulting from obesity. We studied the effects of a polyphenol-rich grape extract supplementation on the plasma metabolome during an overfeeding intervention in adults, in two randomized parallel controlled clinical trials. Methods: Blood plasma samples from 40 normal weight to overweight male adults, submitted to a 31-day overfeeding (additional 50% of energy requirement by a high calorie-high fructose diet), given either 2 g/day grape polyphenol extract or a placebo at 0, 15, 21, and 31 days were analyzed (Lyon study). Samples from a similarly designed trial on females (20 subjects) were collected in parallel (Lausanne study). Nuclear magnetic resonance (NMR)-based metabolomics was conducted to characterize metabolome changes induced by overfeeding and associated effects from polyphenol supplementation. The clinical trials are registered under the numbers NCT02145780 and NCT02225457 at ClinicalTrials.gov. Results: Changes in plasma levels of many metabolic markers, including branched chain amino acids (BCAA), ketone bodies and glucose in both placebo as well as upon polyphenol intervention were identified in the Lyon study. Polyphenol supplementation counterbalanced levels of BCAA found to be induced by overfeeding. These results were further corroborated in the Lausanne female study. Conclusion: Administration of grape polyphenol-rich extract over 1 month period was associated with a protective metabolic effect against overfeeding in adults.

Interaction of Diet/Lifestyle Intervention and TCF7L2 Genotype on Glycemic Control and Adiposity among Overweight or Obese Adults: Big Data from Seven Randomized Controlled Trials Worldwide.

Objective. The strongest locus which associated with type 2 diabetes (T2D) by the common variant rs7903146 is the transcription factor 7-like 2 gene (TCF7L2). We aimed to quantify the interaction of diet/lifestyle interventions and the genetic effect of TCF7L2 rs7903146 on glycemic traits, body weight, or waist circumference in overweight or obese adults in several randomized controlled trials (RCTs).Methods. From October 2016 to May 2018, a large collaborative analysis was performed by pooling individual-participant data from 7 RCTs. These RCTs reported changes in glycemic control and adiposity of the variant rs7903146 after dietary/lifestyle-related interventions in overweight or obese adults. Gene treatment interaction models which used the genetic effect encoded by the allele dose and common covariates were applicable to individual participant data in all studies.Results. In the joint analysis, a total of 7 eligible RCTs were included (n=4,114). Importantly, we observed a significant effect modification of diet/lifestyle-related interventions on the TCF7L2 variant rs7903146 and changes in fasting glucose. Compared with the control group, diet/lifestyle interventions were related to lower fasting glucose by -3.06 (95% CI, -5.77 to -0.36) mg/dL (test for heterogeneity and overall effect: I2=45.1%, p<0.05; z=2.20, p=0.028) per one copy of the TCF7L2 T risk allele. Furthermore, regardless of genetic risk, diet/lifestyle interventions were associated with lower waist circumference. However, there was no significant change for diet/lifestyle interventions in other glycemic control and adiposity traits per one copy of TCF7L2 risk allele.Conclusions. Our findings suggest that carrying the TCF7L2 T risk allele may have a modestly greater benefit for specific diet/lifestyle interventions to improve the control of fasting glucose in overweight or obese adults.

Convergent evidence identifying MAP/microtubule affinity-regulating kinase 1 (MARK1) as a susceptibility gene for autism.

Autism spectrum disorders (ASDs) are common, heritable, but genetically heterogeneous neurodevelopmental conditions. We recently defined a susceptibility locus for ASDs on chromosome 1q41-q42. High-resolution single-nucleotide polymorphisms (126 SNPs) genotyping across the chromosome 1q41-q42 region, followed by a MARK1 (microtubule affinity-regulating kinase 1)-tagged-SNP association study in 276 families with autism from the Autism Genetic Research Exchange, showed that several SNPs within the MARK1 gene were significantly associated with ASDs by transmission disequilibrium tests. Haplotype rs12740310*C-rs3737296*G-rs12410279*A was overtransmitted (P(corrected)= 0.0016), with a relative risk for autism of 1.8 in homozygous carriers. Furthermore, ASD-associated SNP rs12410279 modulates the level of transcription of MARK1. We found that MARK1 was overexpressed in the prefrontal cortex (BA46) but not in cerebellar granule cells, on postmortem brain tissues from patients. MARK1 displayed an accelerated evolution along the lineage leading to humans, suggesting possible involvement of this gene in cognition. MARK1 encodes a kinase-regulating microtubule-dependent transport in axons and dendrites. Both overexpression and silencing of MARK1 resulted in significantly shorter dendrite length in mouse neocortical neurons and modified dendritic transport speed. As expected for a gene encoding a key polarity determinant Par-1 protein kinase, MARK1 is involved in axon-dendrite specification. Thus, MARK1 overexpression in humans may be responsible for subtle changes in dendritic functioning.

Evaluating diagnostic accuracy of genetic profiles in affected offspring families.

Diagnostic accuracy of a genetic test involving multiple disease genes is evaluated using sensitivity and specificity. For estimation, data from both affected and unaffected subjects are required. For early onset diseases, such as autism spectrum disorder (ASD), only data from families with affected offspring are available. To enable estimation of specificity when no data for unaffected offspring are available (single affected offspring, SAO, data), we combine the pseudocontrol method of Cordell and Clayton (Am. J. Hum. Genet. 2002; 70:124-141) with the approach of DeLong et al. (Biometrics 1985; 41:947-958) in a logistic regression model for disease outcome with a risk score (RS) constructed from genotype information as prognostic variable. The area under the receiver operating characteristic curve (AUC) is then computed using the non-parametric Mann-Whitney method. Extensive simulation studies show that, analogous to other approaches utilizing pseudocontrols, the resulting estimates of AUC using SAO data are slightly conservative when compared with the estimates computed using the full population-based data. The method is illustrated using data from a study of ASD.