Genome-wide association analysis of plasma lipidome identifies 495 genetic associations.

The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.

Effect of biological sex on human circulating lipidome: An overview of the literature.

Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.

Early ascending growth is associated with maternal lipoprotein profile during mid and late pregnancy and in cord blood.

INTRODUCTION: Intrauterine conditions and accelerating early growth are associated with childhood obesity. It is unknown, whether fetal programming affects the early growth and could alterations in the maternal-fetal metabolome be the mediating mechanism. Therefore, we aimed to assess the associations between maternal and cord blood metabolite profile and offspring early growth. METHODS: The RADIEL study recruited 724 women at high risk for gestational diabetes mellitus (GDM) BMI ≥ 30 kg/m2 and/or prior GDM) before or in early pregnancy. Blood samples were collected once in each trimester, and from cord. Metabolomics were analyzed by targeted nuclear magnetic resonance (NMR) technique. Following up on offsprings' first 2 years growth, we discovered 3 distinct growth profiles (ascending n = 80, intermediate n = 346, and descending n = 146) by using latent class mixed models (lcmm). RESULTS: From the cohort of mother-child dyads with available growth profile data (n = 572), we have metabolomic data from 232 mothers from 1st trimester, 271 from 2nd trimester, 277 from 3rd trimester and 345 from cord blood. We have data on 220 metabolites in each trimester and 70 from cord blood. In each trimester of pregnancy, the mothers of the ascending group showed higher levels of VLDL and LDL particles, and lower levels of HDL particles (p < 0.05). When adjusted for gestational age, birth weight, sex, delivery mode, and maternal smoking, there was an association with ascending profile and 2nd trimester total cholesterol in HDL2, 3rd trimester total cholesterol in HDL2 and in HDL, VLDL size and ratio of triglycerides to phosphoglycerides (TG/PG ratio) in cord blood (p ≤ 0.002). CONCLUSION: Ascending early growth was associated with lower maternal total cholesterol in HDL in 2nd and 3rd trimester, and higher VLDL size and more adverse TG/PG ratio in cord blood. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, http://www. CLINICALTRIALS: com , NCT01698385.

Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids.

Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.

Quantitative online survey of self-perceived knowledge and knowledge gaps of medicines research and development among Finnish general public.

OBJECTIVES: This study explored self-reported knowledge and interest to learn more about medicines research, development and health technology assessment among Finnish general public. It also aimed to define possible knowledge gaps and needs for public education regarding these topics. DESIGN: Online survey with 503 participants. The questionnaire was originally developed as a part of the Needs Assessment Work Package of the European Patients' Academy on Therapeutic Innovation Project. The survey was carried out in Finland in 2019. METHODS: The survey was conducted as an online survey by Kantar TNS Gallup Forum online panel. The data were analysed by using the freely available programming language R. Relationships between the demographic characteristics (such as age, gender and education level) of respondents and their knowledge or interest in medicines research and development were determined using Pearson's χ2 tests. Statistically significant responses of demographic characteristics in the respondents' knowledge or interest in medicines research were determined by logistic regression. RESULTS: Of the 503 respondents (age 16-64) only 12% reported having good or very good knowledge of medicines research and development in general. Regarding health technology assessment, pharmacoeconomics and regulation, the percentage of respondents reporting good or very good knowledge was as low as 8%. Respondents were most interested in learning more about predictive and personalised medicine (47%) and least interested in medicines regulation (30%) and pharmacoeconomics (31%). CONCLUSIONS: Self-reported knowledge about medicines research and development and health technology assessment appears to be very low in Finland. Patient and public participation is recognised as an important and essential element in up-to-date medical research and assessment of new treatments. In order to participate as an active and equal partner in these processes, the public needs more information and education in these topics.

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases.

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

MetaPhat: Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics.

BACKGROUND: Multivariate testing tools that integrate multiple genome-wide association studies (GWAS) have become important as the number of phenotypes gathered from study cohorts and biobanks has increased. While these tools have been shown to boost statistical power considerably over univariate tests, an important remaining challenge is to interpret which traits are driving the multivariate association and which traits are just passengers with minor contributions to the genotype-phenotypes association statistic. RESULTS: We introduce MetaPhat, a novel bioinformatics tool to conduct GWAS of multiple correlated traits using univariate GWAS results and to decompose multivariate associations into sets of central traits based on intuitive trace plots that visualize Bayesian Information Criterion (BIC) and P-value statistics of multivariate association models. We validate MetaPhat with Global Lipids Genetics Consortium GWAS results, and we apply MetaPhat to univariate GWAS results for 21 heritable and correlated polyunsaturated lipid species from 2,045 Finnish samples, detecting seven independent loci associated with a cluster of lipid species. In most cases, we are able to decompose these multivariate associations to only three to five central traits out of all 21 traits included in the analyses. We release MetaPhat as an open source tool written in Python with built-in support for multi-processing, quality control, clumping and intuitive visualizations using the R software. CONCLUSION: MetaPhat efficiently decomposes associations between multivariate phenotypes and genetic variants into smaller sets of central traits and improves the interpretation and specificity of genome-phenome associations. MetaPhat is freely available under the MIT license at: https://sourceforge.net/projects/meta-pheno-association-tracer.

Genetic architecture of human plasma lipidome and its link to cardiovascular disease.

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias.

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol ( LDL -C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL -C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL -C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL -C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3×10-56). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL -C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL -C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

A comparative evaluation of intraoral and extraoral digital impressions: An in vivo study.

AIM: The accuracy of a dental impression is determined by two factors: "trueness" and "precision." The scanners used in dentistry are relatively new in market, and very few studies have compared the "precision" and "trueness" of intraoral scanner with the extraoral scanner. The aim of this study was to evaluate and compare accuracy of intraoral and extraoral digital impressions. MATERIALS AND METHODS: Ten dentulous participants (male/female) aged 18-45 years with an asymptomatic endodontically treated mandibular first molars with adjacent teeth present were selected for this study. The prepared test tooth was measured using a digital Vernier caliper to obtain reference datasets. The tooth was then scanned using the intraoral scanner, and the extraoral scans were obtained using the casts made from the impressions. The datasets were divided into four groups and then statistically analyzed. The test tooth preparation was done, and dimples were made using a round diamond point on the bucco-occlusal, mesio-occlusal, disto-occlusal, and linguo-occlusal lines angles, and these were used to obtain reference datasets intraorally using a digital Vernier caliper. The test tooth was then scanned with the IO scanner (CS 3500, Carestream dental) thrice and also impressions were made using addition silicone impression material (3M™ ESPE) and dental casts were poured in Type IV dental stone (Kalrock-Kalabhai Karson India Pvt. Ltd., India) which were later scanned with the EO scanner (LAVA™ Scan ST Design system [3M™ ESPE]) thrice. The Datasets obtained from Intraoral and Extraoral scanner were exported to Dental Wings software and readings were obtained. Repeated measures ANOVA test was used to compare differences between the groups and independent t-test for comparison between the readings of intraoral and extraoral scanner. Least significant difference test was used for comparison between reference datasets with intraoral and extraoral scanner, respectively. A level of statistical significance of P < 0.05 was set. RESULTS: The precision values ranged from 20.7 to 33.35 µm for intraoral scanner and 19.5 to 37 µm for extraoral scanner. The mean deviations for intraoral scanner were 19.6 µm mesiodistally (MD) and 16.4 µm buccolingually (BL) and 24.0 µm MD and 22.5 µm BL for extraoral scanner. The mean values of the intraoral scanner (413 µm) for trueness were closest to the actual measurements (459 µm) than the extraoral scanner (396 µm). CONCLUSION: The intraoral scanner showed higher "precision" and "trueness" values when compared with the extraoral scanner.

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

BACKGROUND: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. METHODS: Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. RESULTS: Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. CONCLUSIONS: People express an "omic personality" consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

Genetic studies of type 2 diabetes in South Asians: a systematic overview.

Diabetes Mellitus, which affects 366 million people worldwide, is a leading cause of mortality, morbidity, and loss of quality of life. South Asians, comprising 24% of the world's population, suffer a large burden of type 2 diabetes. With intriguing risk phenotypes, unique environmental triggers, and potential genetic predisposition, South Asians offer a valuable resource for investigating the pathophysiology of type 2 diabetes. Genomics has proven its potential to underpin some of the etiology of type 2 diabetes by identifying a number of susceptibility genes, but such data are scarce and unclear in South Asians. We present a systematic review of studies on the genetic basis of type 2 diabetes or its complications in South Asians published between 1987-2012, and discuss the findings and limitations of the available data. Of the 91 eligible studies meeting our inclusion criteria, a vast majority included Indian populations, followed by a few in those of Pakistani origin, while other South Asian countries were generally under-represented. Though a large number of studies focused on the replication of findings from genome-wide association studies (GWAS) in European populations, a few studies explored new genes and pathways along with GWAS in South Asians and suggested the potential to unravel population- specific susceptibility genes in this population. We find encouraging improvements in study designs, sample sizes and the numbers of genetic variants investigated over the last five years, which reflect the existing capacity and scope for large-scale genetic studies in South Asians.

A Longitudinal Study of Health Improvement in the Atlanta CHDWB Wellness Cohort.

The Center for Health Discovery and Wellbeing (CHDWB) is an academic program designed to evaluate the efficacy of clinical self-knowledge and health partner counseling for development and maintenance of healthy behaviors. This paper reports on the change in health profiles for over 90 traits, measured in 382 participants over three visits in the 12 months following enrolment. Significant changes in the desired direction of improved health are observed for many traits related to cardiovascular health, including BMI, blood pressure, cholesterol, and arterial stiffness, as well as for summary measures of physical and mental health. The changes are most notable for individuals in the upper quartile of baseline risk, many of whom showed a positive correlated response across clinical categories. By contrast, individuals who start with more healthy profiles do not generally show significant improvements and only a modest impact of targeting specific health attributes was observed. Overall, the CHDWB model shows promise as an effective intervention particularly for individuals at high risk for cardiovascular disease.

Whole genome sequencing in support of wellness and health maintenance.

BACKGROUND: Whole genome sequencing is poised to revolutionize personalized medicine, providing the capacity to classify individuals into risk categories for a wide range of diseases. Here we begin to explore how whole genome sequencing (WGS) might be incorporated alongside traditional clinical evaluation as a part of preventive medicine. The present study illustrates novel approaches for integrating genotypic and clinical information for assessment of generalized health risks and to assist individuals in the promotion of wellness and maintenance of good health. METHODS: Whole genome sequences and longitudinal clinical profiles are described for eight middle-aged Caucasian participants (four men and four women) from the Center for Health Discovery and Well Being (CHDWB) at Emory University in Atlanta. We report multivariate genotypic risk assessments derived from common variants reported by genome-wide association studies (GWAS), as well as clinical measures in the domains of immune, metabolic, cardiovascular, musculoskeletal, respiratory, and mental health. RESULTS: Polygenic risk is assessed for each participant for over 100 diseases and reported relative to baseline population prevalence. Two approaches for combining clinical and genetic profiles for the purposes of health assessment are then presented. First we propose conditioning individual disease risk assessments on observed clinical status for type 2 diabetes, coronary artery disease, hypertriglyceridemia and hypertension, and obesity. An approximate 2:1 ratio of concordance between genetic prediction and observed sub-clinical disease is observed. Subsequently, we show how more holistic combination of genetic, clinical and family history data can be achieved by visualizing risk in eight sub-classes of disease. Having identified where their profiles are broadly concordant or discordant, an individual can focus on individual clinical results or genotypes as they develop personalized health action plans in consultation with a health partner or coach. CONCLUSION: The CHDWB will facilitate longitudinal evaluation of wellness-focused medical care based on comprehensive self-knowledge of medical risks.

Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21.

Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes-associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻9). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.

Strong influence of variants near MC4R on adiposity in children and adults: a cross-sectional study in Indian population.

Common variants near melanocortin 4 receptor (MC4R) gene are shown to be associated with adiposity but have varied effects in different age groups. Among Indians, studies have shown association of these variants with obesity in adults, but their association in children is yet to be confirmed. We evaluated association of rs17782313 and rs12970134 near MC4R with adiposity and related traits in Indians including 1362 children and 4077 adults (consisting of 2049 diabetic and 2028 nondiabetic adult subjects). Both variants rs17782313 and rs12970134 showed strong association with adiposity measures (weight, body mass index and waist circumference) in children (P-range 7.6 × 10(-5)-3.8 × 10(-12)) and nominal association in nondiabetic adults (P-range 0.05-0.003). Effect sizes on adiposity measures in children (ß range 0.22-0.26 Z-score) were ~3-fold higher compared with adults (ß range 0.06-0.08). The minor alleles of both variants showed borderline association (P-range 0.08-0.04) with risk of type 2 diabetes in adults. Meta-analysis of rs12970134 in >12 000 Indian adults corroborated its association with adiposity (P≤2.2 × 10(-9)), homeostasis model assessment-estimated insulin resistance (P=4.0 × 10(-5)) and type 2 diabetes (P=0.003) with only moderate heterogeneity, suggesting similar effect on adult Indians residing in different geographical regions. In conclusion, the study demonstrates association of variants near MC4R with obesity and related traits in Indian children and adults, with higher impact during childhood.

Geographical, environmental and pathophysiological influences on the human blood transcriptome.

Gene expression variation provides a read-out of both genetic and environmental influences on gene activity. Geographical, genomic and sociogenomic studies have highlighted how life circumstances of an individual modify the expression of hundreds and in some cases thousands of genes in a co-ordinated manner. This review places such results in the context of a conserved set of 90 transcripts known as Blood Informative Transcripts (BIT) that capture the major conserved components of variation in the peripheral blood transcriptome. Pathophysiological states are also shown to associate with the perturbation of transcript abundance along the major axes. Discussion of false negative rates leads us to argue that simple significance thresholds provide a biased perspective on assessment of differential expression that may cloud the interpretation of studies with small sample sizes.

Common variants of FTO are associated with childhood obesity in a cross-sectional study of 3,126 urban Indian children.

BACKGROUND: FTO variants are robustly associated with obesity and related traits in many population and shown to have variable impact during life course. Although studies have shown association of FTO variants with adiposity in adult Indian, its association in Indian children is yet to be confirmed. METHODS: Here we examined association of FTO variants (rs9939609 and rs8050136) with obesity and related anthropometric and biochemical traits in 3,126 Indian children (aged 11-17 years) including 2,230 normal-weight and 896 over-weight/obese children. We also compared effects observed in the present study with that observed in previous studies on South Asian adults and children of other ethnic groups. RESULTS: The variant rs9939609 showed significant association with risk of obesity [OR = 1.21, P = 2.5 × 10(-3)] and its measures BMI, weight, waist circumference and hip circumference [ß range = 0.11 to 0.14 Z-score units; P range = 1.3 × 10(-4) to 1.6 × 10(-7)] in children. The observed effect sizes in Indian children were similar to those reported for European children. Variant rs9939609 explained 0.88% of BMI variance in Indian children. The effect sizes of rs9939609 on BMI and WC were ~2 fold higher in children than adults. Interestingly rs9939609 was also associated with serum levels of thyroid stimulating hormone (TSH) [ß = 0.10 Z-score, P = 5.8 × 10(-3)]. The other variant rs8050136 was in strong linkage disequilibrium with rs9939609 (r(2) = 0.97) and provided similar association results. CONCLUSION: The study provides first report of association of FTO variants with obesity and related anthropometric traits in Indian children with higher impact in children compared to adults. We also demonstrated association of FTO variant with serum levels of TSH, indicating putative influence of FTO in hypothalamic-pituitary-thyroid axis.

Genetic variant of AMD1 is associated with obesity in urban Indian children.

BACKGROUND: Hyperhomocysteinemia is regarded as a risk factor for cardiovascular diseases, diabetes and obesity. Manifestation of these chronic metabolic disorders starts in early life marked by increase in body mass index (BMI). We hypothesized that perturbations in homocysteine metabolism in early life could be a link between childhood obesity and adult metabolic disorders. Thus here we investigated association of common variants from homocysteine metabolism pathway genes with obesity in 3,168 urban Indian children. METHODOLOGY/PRINCIPAL FINDINGS: We genotyped 90 common variants from 18 genes in 1,325 children comprising of 862 normal-weight (NW) and 463 over-weight/obese (OW/OB) children in stage 1. The top signal obtained was replicated in an independent sample set of 1843 children (1,399 NW and 444 OW/OB) in stage 2. Stage 1 association analysis revealed association between seven variants and childhood obesity at P<0.05, but association of only rs2796749 in AMD1 [OR = 1.41, P = 1.5×10(-4)] remained significant after multiple testing correction. Association of rs2796749 with childhood obesity was validated in stage 2 [OR = 1.28, P = 4.2×10(-3)] and meta-analysis [OR = 1.35, P = 1.9×10(-6)]. AMD1 variant rs2796749 was also associated with quantitative measures of adiposity and plasma leptin levels that was also replicated and corroborated in combined analysis. CONCLUSIONS/SIGNIFICANCE: Our study provides first evidence for the association of AMD1 variant with obesity and plasma leptin levels in children. Further studies to confirm this association, its functional significance and mechanism of action need to be undertaken.

Elevated level of C-reactive protein is associated with risk of prediabetes in Indians.

BACKGROUND: Relationship of high sensitivity C-reactive protein (hsCRP) with prediabetes has not been explored extensively in Indians. Here we sought to investigate the association of hsCRP levels with prediabetes, as represented by impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), and the influence of risk factors like obesity, decreased HDL cholesterol, hypertension, family history of diabetes and current smoking habit on the relationship. METHODS: A cross-sectional study on 1726 Indians, comprising of 1276 individuals with normal glucose tolerance (NGT), 250 IFG and 200 IGT individuals. Subjects were defined according to WHO criteria based on fasting plasma and 2 h glucose levels. RESULTS: Median levels of hsCRP were significantly higher in IFG (2.20 mg/l) and IGT (2.32 mg/l) compared to NGT (1.64 mg/l) subjects. Individuals with high risk hsCRP levels (>3 mg/l) had an odds ratio (OR) (95% confidence interval (CI)) of 2.60 (1.56-5.34) [P=1.3×10(-4)] for IGT after adjusting the effect of age, sex, medication, body mass index (BMI), waist circumference (WC) and risk factors like decreased high-density lipoprotein cholesterol (HDL-cholesterol), hypertension, family history of diabetes and current smoking. Significant increase in risk of IGT was found with a unit increase in natural log transformed hsCRP levels after adjustment for covariates [OR (95%CI)=1.57 (1.27-1.94), P=3.0×10(-5)]. When subjects were stratified on the basis of risk factors, we found stronger association of elevated hsCRP levels with risk of IFG and IGT in subjects having HDL-cholesterol ≤50 mg/dl and with hypertension. CONCLUSIONS: Our study demonstrates that elevated hsCRP levels are independently associated with risk of IFG and IGT in Indians.