EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children

Association Study of a Comprehensive Panel of Neuropeptide-Related Polymorphisms Suggest Potential Roles in Verbal Learning and Memory

Neuropeptides are mostly expressed in regions of the brain responsible for learning and memory and are centrally involved in cognitive pathways. The majority of neuropeptide research has been performed in animal models; with acknowledged differences between species, more research into the role of neuropeptides in humans is necessary to understand their contribution to higher cognitive function. In this study, we investigated the influence of genetic polymorphisms in neuropeptide genes on verbal learning and memory. Variants in genes encoding neuropeptides and neuropeptide receptors were tested for association with learning and memory measures using the Hopkins Verbal Learning Test-Revised (HVLT-R) in a healthy cohort of individuals (n = 597). The HVLT-R is a widely used task for verbal learning and memory assessment and provides five sub-scores: recall, delay, learning, retention, and discrimination. To determine the effect of candidate variants on learning and memory performance, genetic association analyses were performed for each HVLT-R sub-score with over 1300 genetic variants from 124 neuropeptide and neuropeptide receptor genes, genotyped on Illumina OmniExpress BeadChip arrays. This targeted analysis revealed numerous suggestive associations between HVLT-R test scores and neuropeptide and neuropeptide receptor gene variants; candidates include the SCG5, IGFR1, GALR1, OXTR, CCK, and VIPR1 genes. Further characterization of these genes and their variants will improve our understanding of the genetic contribution to learning and memory and provide insight into the importance of the neuropeptide network in humans.

Development of genome-wide association studies on childhood obesity and its indicators: A scoping review and enrichment analysis

BACKGROUND

The progress of genome-wide association studies (GWAS) in childhood obesity and its indicators is challenging and there are differences in genetic studies in children and adults.

OBJECTIVE

To illustrate the history of the development of GWAS in childhood obesity and its indicators and summarize the GWAS loci.

METHODS

PubMed, Web of Science, Embase and GWAS Catalog databases were systematically searched from 1 January 2005 to 19 October 2022 for literature related to GWAS of childhood BMI, body fatness and obesity. The nearest genes were used as positional genes to perform gene set analyses including the enrichment of pathways, tissues and diseases.

RESULTS

Twenty articles published between 2007 and 2021 were included in this scoping review, which identified 116 SNPs reaching genome-wide significance with childhood BMI (n = 50), body fatness (n = 31) and obesity (n = 35). The study populations were European in 16 studies, non-European in three studies (1 East Asian; 1 American; 1 Mexican) and trans-ancestry in one study. Several enriched pathways, tissues and diseases were identified through enrichment analysis of genes associated with childhood obesity and its indicators.

CONCLUSIONS

The innovations in tools and methods enable GWAS to better explore the genetic characteristics of obesity in children and adolescents. However, the number of GWAS in American, Asian and African populations is limited compared to the European population.

Association between the cashmere production performance, milk production performance, and body size traits and polymorphism of COL6A5 and LOC102181374 genes in Liaoning cashmere goats

The purpose of this study was to analyze the relationship between COL6A5 (collagen type VI alpha 5 chain) and LOC102181374 (alcohol dehydrogenase 1) genes and the production performance of Liaoning cashmere goats by single nucleotide polymorphism (SNP). We have searched for SNP loci of COL6A5 and LOC102181374 genes through sequence alignment and PCR experiments, and have used SPSS and SHEsis software to analyze production data. We obtained five SNP loci in total, including three SNP loci (G50985A, G51140T, G51175A) in COL6A5 gene and two SNP loci (A10067G, T10108C) in LOC102181374 gene. The genotypes G50985A (AG), G51140T (GT), G51175A (AA), A10067G (AA), and T10108C (CC) of these loci have certain advantages in improving the production performance of Liaoning cashmere goats. The haplotype combinations that can improve production performance in COL6A5 gene were H1H5:AGGGAG, H4H4:GGGGAA, and H4H4:GGGGAA. H3H3:GGCC and H2H4:AGTT were the dominant combinations in LOC102181374 gene. At G51175A and A10067G loci, we found that H1H2:AAAG and H1H3:AGAA have dominant effects. These results may provide some support for the molecular breeding of production traits in Liaoning cashmere goats.

Identification and validation of candidate clinical signatures of apolipoprotein L isoforms in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide with an increasing number of new cases each year. Apolipoprotein (APOL) isoforms have been explored for their associations with HCC.The GSE14520 cohort was used for training data; The Cancer Genome Atlas (TCGA) database was used for validated data. Diagnostic, prognostic significance and mechanisms were explored using these cohorts. Risk score models and nomograms were constructed using prognosis-related isoforms and clinical factors for survival prediction. Oncomine and HCCDB databases were further used for validation of diagnostic, prognostic significance. APOL1, 3, and 6 were differentially expressed in two cohorts (all P ≤ 0.05). APOL1 and APOL6 had diagnostic capacity whereas APOL3 and APOL6 had prognostic capacity in two cohorts (areas under curves [AUCs] > 0.7, P ≤ 0.05). Mechanism studies demonstrated that APOL3 and APOL6 might be involved in humoral chemokine signaling pathways (all P ≤ 0.05). Risk score models and nomograms were constructed and validated for survival prediction of HCC. Moreover, diagnostic values of APOL1 and weak APOL6 were validated in Oncomine database (AUC > 0.700, 0.694); prognostic values of APOL3 and APOL6 were validated in HCCDB database (all P < 0.05). Differentially expressed APOL1 and APOL6 might be diagnostic biomarkers; APOL3 and APOL6 might be prognostic biomarkers of RFS and OS for HCC via chemokine signaling pathways.

The Impact of ACEs on BMI: An Investigation of the Genotype-Environment Effects of BMI

Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen shown to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events, to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: 1) the effect of ACEs on BMI in the absence of genetics; 2) the effect of genotype-environment interactions on BMI; 3) how these gene-environment interactions differ from standard genetic associations of BMI. The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.

"GENYAL" Study to Childhood Obesity Prevention: Methodology and Preliminary Results

Objective

This article describes the methodology and summarizes some preliminary results of the GENYAL study aiming to design and validate a predictive model, considering both environmental and genetic factors, that identifies children who would benefit most from actions aimed at reducing the risk of obesity and its complications.

Design

The study is a cluster randomized clinical trial with 5-year follow-up. The initial evaluation was carried out in 2017. The schools were randomly split into intervention (nutritional education) and control schools. Anthropometric measurements, social and health as well as dietary and physical activity data of schoolchildren and their families are annually collected. A total of 26 single nucleotide polymorphisms (SNPs) were assessed. Machine Learning models are being designed to predict obesity phenotypes after the 5-year follow-up.

Settings

Six schools in Madrid.

Participants

A total of 221 schoolchildren (6-8 years old).

Results

Collected results show that the prevalence of excess weight was 19.0, 25.4, and 32.2% (according to World Health Organization, International Obesity Task Force and Orbegozo Foundation criteria, respectively). Associations between the nutritional state of children with mother BMI [β = 0.21 (0.13-0.3), p (adjusted) <0.001], geographical location of the school [OR = 2.74 (1.24-6.22), p (adjusted) = 0.06], dairy servings per day [OR = 0.48 (0.29-0.75), p (adjusted) = 0.05] and 8 SNPs [rs1260326, rs780094, rs10913469, rs328, rs7647305, rs3101336, rs2568958, rs925946; p (not adjusted) <0.05] were found.

Conclusions

These baseline data support the evidence that environmental and genetic factors play a role in the development of childhood obesity. After 5-year follow-up, the GENYAL study pretends to validate the predictive model as a new strategy to fight against obesity.

Clinical Trial Registration

This study has been registered in ClinicalTrials.gov with the identifier NCT03419520, https://clinicaltrials.gov/ct2/show/NCT03419520.

Novel recessive locus for body mass index in childhood asthma

Most genome-wide association studies of obesity and body mass index (BMI) have so far assumed an additive mode of inheritance in their analysis, although association testing supports a recessive effect for some of the established loci, for example, rs1421085 in FTO In two whole-genome sequencing (WGS) studies of children with asthma and their parents (892 Costa Rican trios and 286 North American trios), we discovered an association between a locus (rs9292139) in LOC102724122 and BMI that reaches genome-wide significance under a recessive model in the combined analysis. As the association does not achieve significance under an additive model, our finding illustrates the benefits of the recessive model in WGS analyses.

Innate-Immunity Genes in Obesity

The main functions of adipose tissue are thought to be storage and mobilization of the body’s energy reserves, active and passive thermoregulation, participation in the spatial organization of internal organs, protection of the body from lipotoxicity, and ectopic lipid deposition. After the discovery of adipokines, the endocrine function was added to the above list, and after the identification of crosstalk between adipocytes and immune cells, an immune function was suggested. Nonetheless, it turned out that the mechanisms underlying mutual regulatory relations of adipocytes, preadipocytes, immune cells, and their microenvironment are complex and redundant at many levels. One possible way to elucidate the picture of adipose-tissue regulation is to determine genetic variants correlating with obesity. In this review, we examine various aspects of adipose-tissue involvement in innate immune responses as well as variants of immune-response genes associated with obesity.

Association of Genetic Variants With Body-Mass Index and Blood Pressure in Adolescents: A Replication Study

The strong correlation between adiposity and blood pressure (BP) might be explained in part by shared genetic risk factors. A recent study identified three nucleotide variants [rs16933812 (PAX5), rs7638110 (MRPS22), and rs9930333 (FTO)] associated with both body mass index (BMI) and systolic blood pressure (SBP) in adolescents age 12-18years. We attempted to replicate these findings in a sample of adolescents of similar age. A total of 713 adolescents were genotyped and had anthropometric indicators and blood pressure measured at age 13, 15, 17, and 24years. Using linear mixed models, we assessed associations of these variants with BMI and SBP. In our data, rs9930333 (FTO) was associated with body mass index, but not systolic blood pressure. Neither rs16933812 (PAX5) nor rs7638110 (MRPS22) were associated with body mass index or systolic blood pressure. Although, differences in phenotypic definitions and in genetic architecture across populations may explain some of the discrepancy across studies, nucleotide variant selection in the initial study may have led to false-positive results that could not be replicated.

Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction

Extracellular matrix (ECM) remodeling plays important roles in both white adipose tissue (WAT) and the skeletal muscle (SM) metabolism. Excessive adipocyte hypertrophy causes fibrosis, inflammation, and metabolic dysfunction in adipose tissue, as well as impaired adipogenesis. Similarly, disturbed ECM remodeling in SM has metabolic consequences such as decreased insulin sensitivity. Most of described ECM molecular alterations have been associated with DNA sequence variation, alterations in gene expression patterns, and epigenetic modifications. Among others, the most important epigenetic mechanism by which cells are able to modulate their gene expression is DNA methylation. Epigenome-Wide Association Studies (EWAS) have become a powerful approach to identify DNA methylation variation associated with biological traits in humans. Likewise, Genome-Wide Association Studies (GWAS) and gene expression microarrays have allowed the study of whole-genome genetics and transcriptomics patterns in obesity and metabolic diseases. The aim of this review is to explore the molecular basis of ECM in WAT and SM remodeling in obesity and the consequences of metabolic complications. For that purpose, we reviewed scientific literature including all omics approaches reporting genetic, epigenetic, and transcriptomic (GWAS, EWAS, and RNA-seq or cDNA arrays) ECM-related alterations in WAT and SM as associated with metabolic dysfunction and obesity.

Building a Population Representative Pediatric Biobank: Lessons Learned From the Greater Cincinnati Childhood Cohort

Background: Biobanks can accelerate research by providing researchers with samples and data. However, hospital-based recruitment as a source for controls may create bias as who comes to the hospital may be different from the broader population. Methods: In an effort to broadly improve the quality of research studies and reduce costs and challenges associated with recruitment and sample collection, a group of diverse researchers at Cincinnati Children's Hospital Medical Center led an institution-supported initiative to create a population representative pediatric "Greater Cincinnati Childhood Cohort (GCC)." Participants completed a detailed survey, underwent a brief physician-led physical exam, and provided blood, urine, and hair samples. DNA underwent high-throughput genotyping. Results: In total, 1,020 children ages 3-18 years living in the 7 county Greater Cincinnati Metropolitan region were recruited. Racial composition of the cohort was 84% non-Hispanic white, 15% non-Hispanic black, and 2% other race or Hispanic. Participants exhibited marked demographic and disease burden differences by race. Overall, the cohort was broadly used resulting in publications, grants and patents; yet, it did not meet the needs of all potential researchers. Conclusions: Learning from both the strengths and weaknesses, we propose leveraging a community-based participatory research framework for future broad use biobanking efforts.

Autozygosity influences cardiometabolic disease-associated traits in the AWI-Gen sub-Saharan African study

The analysis of the effects of autozygosity, measured as the change of the mean value of a trait among offspring of genetic relatives, reveals the existence of directional dominance or overdominance. In this study we detect evidence of the effect of autozygosity in 4 out of 13 cardiometabolic disease-associated traits using data from more than 10,000 sub-Saharan African individuals recruited from Ghana, Burkina Faso, Kenya and South Africa. The effect of autozygosity on these phenotypes is found to be sex-related, with inbreeding having a significant decreasing effect in men but a significant increasing effect in women for several traits (body mass index, subcutaneous adipose tissue, low-density lipoproteins and total cholesterol levels). Overall, the effect of inbreeding depression is more intense in men. Differential effects of inbreeding depression are also observed between study sites with different night-light intensity used as proxy for urban development. These results suggest a directional dominant genetic component mediated by environmental interactions and sex-specific differences in genetic architecture for these traits in the Africa Wits-INDEPTH partnership for Genomic Studies (AWI-Gen) cohort.

The Construction and Analysis of the Aberrant lncRNA-miRNA-mRNA Network in Adipose Tissue from Type 2 Diabetes Individuals with Obesity

BACKGROUND

The prevalence of obesity and type 2 diabetes mellitus (T2DM) has become the most serious global public health issue. In recent years, there has been increasing attention to the role of long noncoding RNAs (lncRNAs) in the occurrence and development of obesity and T2DM. The aim of this work was to find new lncRNAs as potential predictive biomarkers or therapeutic targets for obesity and T2DM.

METHODS

In this study, we identified significant differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) between adipose tissue of individuals with obesity and T2DM and normal adipose tissue (absolute log₂FC ≥ 1 and FDR < 0.05). Then, the lncRNA-miRNA interactions predicted by miRcode were further screened with a threshold of MIC > 0.2. Simultaneously, the mRNA-miRNA interactions were explored by miRWalk 2.0. Finally, a ceRNA network consisting of lncRNAs, miRNAs, and mRNAs was established by integrating lncRNA-miRNA interactions and mRNA-miRNA interactions.

RESULTS

Upon comparing adipose tissue from individuals with obesity and T2DM and normal adipose tissues, 364 significant DEmRNAs, including 140 upregulated and 224 downregulated mRNAs, were identified in GSE104674; in addition, 231 significant DEmRNAs, including 146 upregulated and 85 downregulated mRNAs, were identified in GSE133099. GO and KEGG analyses have shown that downregulated DEmRNAs in GSE104674 and GSE133099 were associated with obesity- and T2DM-related biological pathways, such as lipid metabolism, AMPK signaling, and insulin resistance. Furthermore, 28 significant DElncRNAs, including 14 upregulated and 14 downregulated lncRNAs, were found. Based on the predicted lncRNA-miRNA and mRNA-miRNA relationships, we constructed a competitive endogenous RNA (ceRNA) network, including five lncRNAs, ten miRNAs, and 15 mRNAs. KEGG-GSEA analysis revealed that four lncRNAs (FLG-AS1, SNAI3-AS1, AC008147.0, and LINC02015) in the ceRNA network were related to the biological pathways of metabolic diseases.

CONCLUSIONS

Through ceRNA network analysis, our study identified four new lncRNAs that may be used as potential biomarkers and therapeutic targets of obesity and T2DM, thus laying a foundation for future clinical studies.

Polymorphisms in Adipokines in Mexican Children with Obesity

The high prevalence of childhood obesity in Mexico is alarming in the health-science field. We propose to investigate the contribution of adipokines and cytokines polymorphisms and common BMI/obesity-associated loci, revealed in genome-wide association studies in Caucasian adult cohorts, with childhood obesity. This study included 773 Mexican-Mestizo children (5-15 years old) in a case-control study. The polymorphisms included were ADIPOQ (rs6444174), TNF-α (rs1800750), IL-1β (rs1143643), IL-6 (rs1524107; rs2069845), NEGR1 (rs34305371), SEC16B-RASAL2 (rs10913469), TMEM18 (rs6548238; rs7561317), GNPDA2 (rs16857402), LEP (rs2167270), MTCH2 (rs10838738), LGR4-LIN7C-BDNF (rs925946), BCDIN3D-FAIM2 (rs7138803), FTO (rs62033400), MC4R (rs11872992), MC4R (rs17782313), and KCTD15 (rs29942). No significant contribution was found with adipokines and cytokines polymorphisms in this study. Only both TMEM18 (rs6548238; rs7561317) polymorphisms were found associated with obesity (OR=0.5, P=0.008) and were in linkage disequilibrium (r2=0.87). The linear regression showed that the rs7561317 polymorphism of TMEM18 is negatively associated with obesity. This report highlights the influence of TMEM18 in Mexican-Mestizo children obesity, while adipokine and cytokine polymorphisms were not associated with it.

Patterns of genetic structure and adaptive positive selection in the Lithuanian population from high-density SNP data

The analysis of geographically specific regions and the characterization of fine-scale patterns of genetic diversity may facilitate a much better understanding of the microevolutionary processes affecting local human populations. Here we generated genome-wide high-density SNP genotype data in 425 individuals from six geographical regions in Lithuania and combined our dataset with available ancient and modern data to explore genetic population structure, ancestry components and signatures of natural positive selection in the Lithuanian population. Our results show that Lithuanians are a homogenous population, genetically differentiated from neighbouring populations but within the general expected European context. Moreover, we not only confirm that Lithuanians preserve one of the highest proportions of western, Scandinavian and eastern hunter-gather ancestry components found in European populations but also that of an steppe Early to Middle Bronze Age pastoralists, which together configure the genetic distinctiveness of the Lithuanian population. Finally, among the top signatures of positive selection detected in Lithuanians, we identified several candidate genes related with diet (PNLIP, PPARD), pigmentation (SLC24A5, TYRP1 and PPARD) and the immune response (BRD2, HLA-DOA, IL26 and IL22).

The genetic and epigenetic association of LDL Receptor Related Protein 1B (LRP1B) gene with childhood obesity

Low-density lipoprotein Receptor Related Protein 1B (LRP1B) is homologous to the gigantic lipoprotein receptor-related protein 1 that belongs to the family of Low-density lipoprotein receptors. Previous genetic association studies of the LRP1B gene have shown its genetic association with obesity. Through exome sequencing of the LRP1B gene from a childhood severe obesity cohort (n = 692), we found novel single nucleotide polymorphism (rs431809) in intron 4, which has been significantly correlated with both body mass index (BMI) and waist-hip-ratio (WHR). Three methylations of CpG sites (cg141441481, cg01852095 and cg141441470) in the same intron were also significantly correlated with BMI and WHR. All CpG methylations had bimodal patterns, and were dependent on rs431809 genotypes. The genetic influences of obesity on the LRP1B gene may be linked to the interplay of CpG methylations in the same intron. Heritability of SNP interacts with epigenetic crosstalk in LRP1B. Genetic and epigenetic crosstalk of LRP1B gene may be implicated in the prevention and therapeutic approach to childhood obesity.

Prioritizing putative influential genes in cardiovascular disease susceptibility by applying tissue-specific Mendelian randomization

BACKGROUND

The extent to which changes in gene expression can influence cardiovascular disease risk across different tissue types has not yet been systematically explored. We have developed an analysis pipeline that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from a genetic variant to a complex trait.

METHODS

We undertook an expression quantitative trait loci-wide association study to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Fine-mapping was performed to prioritize possible causal variants for detected associations. Two-sample Mendelian randomization (MR) was then applied using findings from genome-wide association studies (GWAS) to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently used Bayesian multiple-trait colocalization to further interrogate the findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility. Finally, we applied our analysis pipeline genome-wide using summary statistics from large-scale GWAS.

RESULTS

Eight genetic loci were associated with changes in gene expression and measures of cardiovascular function. Our MR analysis provided evidence of tissue-specific effects at multiple loci, of which the effects at the ADCY3 and FADS1 loci for body mass index and cholesterol, respectively, were particularly insightful. Multiple-trait colocalization uncovered evidence which suggested that changes in DNA methylation at the promoter region upstream of FADS1/TMEM258 may also affect cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses uncovered evidence of tissue specificity between gene expression in liver tissue and cholesterol levels. Applying our pipeline genome-wide using summary statistics from GWAS uncovered 233 association signals at loci which represent promising candidates for further evaluation.

CONCLUSIONS

Disease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. The approach undertaken in our study can be used to elucidate mechanisms in disease, as well as helping prioritize putative causal genes at associated loci where multiple nearby genes may be co-regulated. Future studies which continue to uncover quantitative trait loci for molecular traits across various tissue and cell types will further improve our capability to understand and prevent disease.

A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci

Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10^-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.

Genetic Variants Associated With Obesity and Insulin Resistance in Hispanic Boys With Nonalcoholic Fatty Liver Disease

BACKGROUND AND OBJECTIVES

Nonalcoholic fatty liver disease (NAFLD) disproportionately affects Hispanic boys. Further, obesity and insulin resistance are major risk factors for NAFLD. No gene localization studies had been performed on children with biopsy-proven NAFLD. This study aims to identify genomic variants associated with increased adiposity and insulin resistance in a population of children with varying histologic severity of NAFLD.

METHODS

We conducted a genome-wide association scan (GWAS) including 624,297 single-nucleotide polymorphisms (SNPs) distributed among all 22 autosomal chromosomes in 234 Hispanic boys (up to 18 years of age) who were consecutively recruited in a prospective cohort study in the Nonalcoholic Steatohepatitis Clinical Research Network Studies. Traits were examined quantitatively using linear regression. SNPs with P value <10 and a minor allele frequency >5% were considered potentially significant.

RESULTS

Evaluated subjects had a median age of 12.0 years, body mass index (BMI) of 31.4, and hemoglobin A1C (Hgb A1C) of 5.3. The prevalence of NAFL, borderline NASH, and definite NASH were 23%, 53%, and 22%, respectively. The GWAS identified 10 SNPs that were associated with BMI z score, 6 within chromosome 2, and 1 within CAMK1D, which has a potential role in liver gluconeogenesis. In addition, the GWAS identified 9 novel variants associated with insulin resistance: HOMA-IR (6) and HbA1c (3).

CONCLUSIONS

This study of Hispanic boys with biopsy-proven NAFLD with increased risk for the metabolic syndrome revealed novel genetic variants that are associated with obesity and insulin resistance.

Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children

OBJECTIVE

To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.

METHODS

Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.

RESULTS

(1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.

CONCLUSIONS

Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.

Association of gene coding variation and resting metabolic rate in a multi-ethnic sample of children and adults

Background

Resting metabolic rates (RMR) vary across individuals. Understanding the determinants of RMR could provide biological insight into obesity and its metabolic consequences such as type 2 diabetes and cardiovascular diseases.

Methods

The present study measured RMR using reference standard indirect calorimetry and evaluated genetic variations from an exome array in a sample of children and adults (N = 262) predominantly of African and European ancestry with a wide range of ages (10 – 67 years old) and body mass indices (BMI; 16.9 – 56.3 kg/m² for adults, 15.1 – 40.6 kg/m2 for children).

Results

Single variant analysis for RMR identified suggestive loci on chromosomes 15 (rs74010762, TRPM1, p-value = 2.7 × 10−6), 1 (rs2358728 and rs2358729, SH3D21, p-values < 5.8x10−5), 17 (AX-82990792, DHX33, 5.5 × 10−5) and 5 (rs115795863 and rs35433829, C5orf33 and RANBP3L, p-values < 8.2 × 10−5). To evaluate the effect of low frequency variations with RMR, we performed gene-based association tests. Our most significant locus was SH3D21 (p-value 2.01 × 10−4), which also contained suggestive results from single-variant analyses. A further investigation of all variants within the reported genes for all obesity-related loci from the GWAS catalog found nominal evidence for association of body mass index (BMI- kg/m²)-associated loci with RMR, with the most significant p-value at rs35433754 (TNKS, p-value = 0.0017).

Conclusions

These nominal associations were robust to adjustment for BMI. The most significant variants were also evaluated using phenome-wide association to evaluate pleiotropy, and genetically predicted gene expression using the summary statistics implicated loci related to in obesity and body composition. These results merit further examination in larger cohorts of children and adults.

Electronic supplementary material

The online version of this article (doi:10.1186/s40608-017-0145-5) contains supplementary material, which is available to authorized users.

Association of timing of menarche with depressive symptoms and depression in adolescence: Mendelian randomisation study

BACKGROUND

Observational studies report associations between early menarche and higher levels of depressive symptoms and depression. However, no studies have investigated whether this association is causal.

AIMS

To determine whether earlier menarche is a causal risk factor for depressive symptoms and depression in adolescence.

METHOD

The associations between a genetic score for age at menarche and depressive symptoms at 14, 17 and 19 years, and depression at 18 years, were examined using Mendelian randomisation analysis techniques.

RESULTS

Using a genetic risk score to indicate earlier timing of menarche, we found that early menarche is associated with higher levels of depressive symptoms at 14 years (odds ratio per risk allele 1.02, 95% CI 1.005-1.04, n = 2404). We did not find an association between the early menarche risk score and depressive symptoms or depression after age 14.

CONCLUSIONS

Our results provide evidence for a causal effect of age at menarche on depressive symptoms at age 14.

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability

OBJECTIVE

Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems.Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org), an online environment supporting the workflow of building, sharing, and validating electronic phenotype algorithms. We analyze the most frequent components used in algorithms and their performance at authoring institutions and secondary implementation sites.

RESULTS

As of June 2015, PheKB contained 30 finalized phenotype algorithms and 62 algorithms in development spanning a range of traits and diseases. Phenotypes have had over 3500 unique views in a 6-month period and have been reused by other institutions. International Classification of Disease codes were the most frequently used component, followed by medications and natural language processing. Among algorithms with published performance data, the median PPV was nearly identical when evaluated at the authoring institutions (n = 44; case 96.0%, control 100%) compared to implementation sites (n = 40; case 97.5%, control 100%).

DISCUSSION

These results demonstrate that a broad range of algorithms to mine electronic health record data from different health systems can be developed with high PPV, and algorithms developed at one site are generally transportable to others.

CONCLUSION

By providing a central repository, PheKB enables improved development, transportability, and validity of algorithms for research-grade phenotypes using health care generated data.

Retrospective Study of Obesity in Children with Down Syndrome

OBJECTIVES

To assess whether children with Down syndrome in the US are at an increased risk for obesity, we determined the obesity prevalence and analyzed obesity development throughout childhood in a cohort of children with Down syndrome. In addition, we analyzed a comorbidity that is associated with Down syndrome and obesity, obstructive sleep apnea syndrome (OSAS).

STUDY DESIGN

This study was a retrospective chart review that evaluated 303 children ages 2 through 18 years with a diagnosis of Down syndrome. All children were patients at Cincinnati Children's Hospital Medical Center with multiple height and weight measurements. To determine obesity burden, the rate of obesity was compared with a local control cohort using contingency tables. Change in obesity rate through time was determined with mixed models. Association of obesity with OSAS was determined with contingency tables.

RESULTS

We evaluated 303 individuals, 47.8% of whom were obese (body mass index ≥95th percentile for age and sex). This was significantly higher than the general pediatric population, which had a 12.1% obesity rate (P < .0001). Body mass index z-scores did not change markedly over time (P = .40). The majority of children with Down syndrome also had OSAS (74.0% of the 177 children who had polysomnography studies). However, OSAS risk was elevated in obese children (risk ratio = 2.4, P = .0015).

CONCLUSIONS

Our results indicate that children with Down syndrome are at a substantial risk for obesity and OSAS. These findings support the need for more aggressive weight management in early childhood and throughout the lifespan.

Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index

A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex- and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value < 5 × 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 × 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index.

BIOFILTER AS A FUNCTIONAL ANNOTATION PIPELINE FOR COMMON AND RARE COPY NUMBER BURDEN

Recent studies on copy number variation (CNV) have suggested that an increasing burden of CNVs is associated with susceptibility or resistance to disease. A large number of genes or genomic loci contribute to complex diseases such as autism. Thus, total genomic copy number burden, as an accumulation of copy number change, is a meaningful measure of genomic instability to identify the association between global genetic effects and phenotypes of interest. However, no systematic annotation pipeline has been developed to interpret biological meaning based on the accumulation of copy number change across the genome associated with a phenotype of interest. In this study, we develop a comprehensive and systematic pipeline for annotating copy number variants into genes/genomic regions and subsequently pathways and other gene groups using Biofilter - a bioinformatics tool that aggregates over a dozen publicly available databases of prior biological knowledge. Next we conduct enrichment tests of biologically defined groupings of CNVs including genes, pathways, Gene Ontology, or protein families. We applied the proposed pipeline to a CNV dataset from the Marshfield Clinic Personalized Medicine Research Project (PMRP) in a quantitative trait phenotype derived from the electronic health record - total cholesterol. We identified several significant pathways such as toll-like receptor signaling pathway and hepatitis C pathway, gene ontologies (GOs) of nucleoside triphosphatase activity (NTPase) and response to virus, and protein families such as cell morphogenesis that are associated with the total cholesterol phenotype based on CNV profiles (permutation p-value < 0.01). Based on the copy number burden analysis, it follows that the more and larger the copy number changes, the more likely that one or more target genes that influence disease risk and phenotypic severity will be affected. Thus, our study suggests the proposed enrichment pipeline could improve the interpretability of copy number burden analysis where hundreds of loci or genes contribute toward disease susceptibility via biological knowledge groups such as pathways. This CNV annotation pipeline with Biofilter can be used for CNV data from any genotyping or sequencing platform and to explore CNV enrichment for any traits or phenotypes. Biofilter continues to be a powerful bioinformatics tool for annotating, filtering, and constructing biologically informed models for association analysis - now including copy number variants.

Genome-wide association study for the interaction between BMR and BMI in obese Korean women including overweight

BACKGROUND/OBJECTIVES

This is the first study to identify common genetic factors associated with the basal metabolic rate (BMR) and body mass index (BMI) in obese Korean women including overweight. This will be a basic study for future research of obese gene-BMR interaction.

SUBJECTS/METHODS

The experimental design was 2 by 2 with variables of BMR and BMI. A genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) was conducted in the overweight and obesity (BMI > 23 kg/m²) compared to the normality, and in women with low BMR (< 1426.3 kcal/day) compared to high BMR. A total of 140 SNPs reached formal genome-wide statistical significance in this study (P < 1 × 10^-4). Surveys to estimate energy intake using 24-h recall method for three days and questionnaires for family history, a medical examination, and physical activities were conducted.

RESULTS

We found that two NRG3 gene SNPs in the 10q23.1 chromosomal region were highly associated with BMR (rs10786764; P = 8.0 × 10^-7, rs1040675; 2.3 × 10^-6) and BMI (rs10786764; P = 2.5 × 10^-5, rs10786764; 6.57 × 10^-5). The other genes related to BMI (HSD52, TMA16, MARCH1, NRG1, NRXN3, and STK4) yielded P <10 × 10^-4. Five new loci associated with BMR and BMI, including NRG3, OR8U8, BCL2L2-PABPN1, PABPN1, and SLC22A17 were identified in obese Korean women (P < 1 × 10^-4). In the questionnaire investigation, significant differences were found in the number of starvation periods per week, family history of stomach cancer, coffee intake, and trial of weight control in each group.

CONCLUSION

We discovered several common BMR- and BMI-related genes using GWAS. Although most of these newly established loci were not previously associated with obesity, they may provide new insights into body weight regulation. Our findings of five common genes associated with BMR and BMI in Koreans will serve as a reference for replication and validation of future studies on the metabolic rate.

A genome-wide association study reveals susceptibility loci for myocardial infarction/coronary artery disease in Saudi Arabs

BACKGROUND

Multiple loci have been identified for coronary artery disease (CAD) by genome-wide association studies (GWAS), but no such studies on CAD incidence has been reported yet for any Middle Eastern population.

METHODS

In this study, we performed a GWAS for CAD and myocardial infarction (MI) incidence in 5668 Saudis of Arab descent using the Affymetrix Axiom Genotyping platform.

RESULTS

We describe SNPs at 16 loci that showed significant (P < 5 × 10(-8)) or suggestive GWAS association (P < 1 × 10(-5)) with CAD or MI, in the ethnic Saudi Arab population. Among the four variants reaching GWAS significance in the present study, the rs10738607_G [0.78(0.71-0.85); p = 2.17E-08] in CDNK2A/B gene was associated with CAD. Two other SNPs on the same gene, rs10757274_G [0.79(0.73-0.86); p = 2.98E-08] and rs1333045_C [0.79(0.73-0.86); p = 1.15E-08] as well as the rs9982601_T [1.38(1.23-1.55); p = 3.49E-08] on KCNE2 were associated with MI. These variants have been previously described in other populations. Several SNPs, including the rs7421388 (PLCL1) and rs12541758 (TRPA1) displaying a suggestive GWAS association (P < 1 × 10(-5)) with CAD as well as rs41411047 (RNF13), rs32793 (PDZD2) and rs4739066 (YTHDF3), similarly showing weak association with MI, were confirmed in an independent dataset. Furthermore, our estimation of heritability of CAD and MI based on observed genome-wide sharing in unrelated Saudi Arabs was approximately 33% and 44%, respectively.

CONCLUSIONS

Our study has identified susceptibility variants for CAD/MI in ethnic Arabs. These findings provide further insights into pathways contributing to the susceptibility for CAD and will enable more comprehensive genetic studies of these diseases in Middle East populations.

LRP1B, BRD2 and CACNA1D: new candidate genes in fetal metabolic programming of newborns exposed to maternal hyperglycemia

AIM

To assess the associations between gestational diabetes mellitus (GDM) and DNA methylation levels at genes related to energy metabolism.

PATIENTS & METHODS

Ten loci were selected from our recent epigenome-wide association study on GDM. DNA methylation levels were quantified by bisulfite pyrosequencing in 80 placenta and cord blood samples (20 exposed to GDM) from an independent birth cohort (Gen3G).

RESULTS

We did not replicate association between DNA methylation and GDM. However, in normoglycemic women, glucose levels were associated with DNA methylation changes at LRP1B and BRD2 and at CACNA1D and LRP1B gene loci in placenta and cord blood, respectively.

CONCLUSION

These results suggest that maternal glucose levels, within the normal range, are associated with DNA methylation changes at genes related to energy metabolism and previously associated with GDM. Maternal glycemia might thus be involved in fetal metabolic programming.

Insights into the Genetic Susceptibility to Type 2 Diabetes from Genome-Wide Association Studies of Obesity-Related Traits

Obesity and type 2 diabetes (T2D) are common and complex metabolic diseases, which are caused by an interchange between environmental and genetic factors. Recently, a number of large-scale genome-wide association studies (GWAS) have improved our knowledge of the genetic architecture and biological mechanisms of these diseases. Currently, more than ~250 genetic loci have been found for monogenic, syndromic, or common forms of T2D and/or obesity-related traits. In this review, we discuss the implications of these GWAS for obesity and T2D, and investigate the overlap of loci for obesity-related traits and T2D, highlighting potential mechanisms that affect T2D susceptibility.

Energy homeostasis genes and breast cancer risk: The influence of ancestry, body size, and menopausal status, the breast cancer health disparities study

BACKGROUND

Obesity and breast cancer risk is multifaceted and genes associated with energy homeostasis may modify this relationship.

METHODS

We evaluated 10 genes that have been associated with obesity and energy homeostasis to determine their association with breast cancer risk in Hispanic/Native American (2111 cases, 2597 controls) and non-Hispanic white (1481 cases, 1585 controls) women.

RESULTS

Cholecystokinin (CCK) rs747455 and proopiomelanocortin (POMC) rs6713532 and rs7565877 (for low Indigenous American (IA) ancestry); CCK rs8192472 and neuropeptide Y (NYP) rs16141 and rs14129 (intermediate IA ancestry); and leptin receptor (LEPR) rs11585329 (high IA ancestry) were strongly associated with multiple indicators of body size. There were no significant associations with breast cancer risk between genes and SNPs overall. However, LEPR was significantly associated with breast cancer risk among women with low IA ancestry (PARTP=0.024); POMC was significantly associated with breast cancer risk among women with intermediate (PARTP=0.015) and high (PARTP=0.012) IA ancestry. The overall pathway was statistically significant for pre-menopausal women with low IA ancestry (PARTP=0.05), as was cocaine and amphetamine regulated transcript protein (CARTPT) (PARTP=0.014) and ghrelin (GHRL) (PARTP=0.007). POMC was significantly associated with breast cancer risk among post-menopausal women with higher IA ancestry (PARTP=0.005). Three SNPs in LEPR (rs6704167, rs17412175, and rs7626141), and adiponectin (ADIPOQ); rs822391) showed significant 4-way interactions (GxExMenopausexAncestry) for multiple indicators of body size among pre-menopausal women.

CONCLUSIONS

Energy homeostasis genes were associated with breast cancer risk; menopausal status, body size, and genetic ancestry influenced this relationship.

Desiderata for computable representations of electronic health records-driven phenotype algorithms

BACKGROUND

Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).

METHODS

A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.

RESULTS

We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.

CONCLUSION

A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis

Objective: We report the first pediatric specific Phenome-Wide Association Study (PheWAS) using electronic medical records (EMRs). Given the early success of PheWAS in adult populations, we investigated the feasibility of this approach in pediatric cohorts in which associations between a previously known genetic variant and a wide range of clinical or physiological traits were evaluated. Although computationally intensive, this approach has potential to reveal disease mechanistic relationships between a variant and a network of phenotypes.

Method: Data on 5049 samples of European ancestry were obtained from the EMRs of two large academic centers in five different genotyped cohorts. Recently, these samples have undergone whole genome imputation. After standard quality controls, removing missing data and outliers based on principal components analyses (PCA), 4268 samples were used for the PheWAS study. We scanned for associations between 2476 single-nucleotide polymorphisms (SNP) with available genotyping data from previously published GWAS studies and 539 EMR-derived phenotypes. The false discovery rate was calculated and, for any new PheWAS findings, a permutation approach (with up to 1,000,000 trials) was implemented.

Results: This PheWAS found a variety of common variants (MAF > 10%) with prior GWAS associations in our pediatric cohorts including Juvenile Rheumatoid Arthritis (JRA), Asthma, Autism and Pervasive Developmental Disorder (PDD) and Type 1 Diabetes with a false discovery rate < 0.05 and power of study above 80%. In addition, several new PheWAS findings were identified including a cluster of association near the NDFIP1 gene for mental retardation (best SNP rs10057309, p = 4.33 × 10⁻⁷, OR = 1.70, 95%CI = 1.38 − 2.09); association near PLCL1 gene for developmental delays and speech disorder [best SNP rs1595825, p = 1.13 × 10⁻⁸, OR = 0.65(0.57 − 0.76)]; a cluster of associations in the IL5-IL13 region with Eosinophilic Esophagitis (EoE) [best at rs12653750, p = 3.03 × 10⁻⁹, OR = 1.73 95%CI = (1.44 − 2.07)], previously implicated in asthma, allergy, and eosinophilia; and association of variants in GCKR and JAZF1 with allergic rhinitis in our pediatric cohorts [best SNP rs780093, p = 2.18 × 10⁻⁵, OR = 1.39, 95%CI = (1.19 − 1.61)], previously demonstrated in metabolic disease and diabetes in adults.

Conclusion: The PheWAS approach with re-mapping ICD-9 structured codes for our European-origin pediatric cohorts, as with the previous adult studies, finds many previously reported associations as well as presents the discovery of associations with potentially important clinical implications.

The genetics of human obesity

The heritability of obesity has long been appreciated and the genetics of obesity has been the focus of intensive study for decades. Early studies elucidating genetic factors involved in rare monogenic and syndromic forms of extreme obesity focused attention on dysfunction of hypothalamic leptin-related pathways in the control of food intake as a major contributor. Subsequent genome-wide association studies of common genetic variants identified novel loci that are involved in more common forms of obesity across populations of diverse ethnicities and ages. The subsequent search for factors contributing to the heritability of obesity not explained by these 2 approaches ("missing heritability") has revealed additional rare variants, copy number variants, and epigenetic changes that contribute. Although clinical applications of these findings have been limited to date, the increasing understanding of the interplay of these genetic factors with environmental conditions, such as the increased availability of high calorie foods and decreased energy expenditure of sedentary lifestyles, promises to accelerate the translation of genetic findings into more successful preventive and therapeutic interventions.

Personalized medicine for chronic, complex diseases: chronic obstructive pulmonary disease as an example

Chronic, complex diseases represent the majority of healthcare utilization and spending in the USA today. Despite this, therapeutics that account for the heterogeneity of these diseases are lacking, begging for more personalized approaches. Improving our understanding of disease phenotypes through retrospective trials of electronic health record data will enable us to better categorize patients. Increased usage of next-generation sequencing will further our understanding of the genetic variants involved in chronic disease. Utilization of data warehousing will be necessary in order to securely handle, integrate and analyze the large sets of data produced with these methods. Finally, increased use of clinical decision support will enable the return of clinically actionable results that physicians can use to apply these personalized approaches.

eMERGEing progress in genomics-the first seven years

The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.