Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae

A Polynesian-specific missense CETP variant alters the lipid profile

Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Māori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies.

A stop-gain variant in BTNL9 is associated with atherogenic lipid profiles

Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here, we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652C>T, p.R218∗; posterior probability = 0.9987) in BTNL9 and both lower HDL-C and greater triglycerides (TGs). Meta-analysis across this and several other cohorts of Polynesian ancestry from Samoa, American Samoa, and Aotearoa New Zealand confirmed the presence of this association (βHDL-C = -1.60 mg/dL, p HDL-C = 7.63 × 10-10; βTG = 12.00 mg/dL, p TG = 3.82 × 10-7). While this variant appears to be Polynesian specific, there is also evidence of association from other multiancestry analyses in this region. This work provides evidence of a previously unexplored contributor to the genetic architecture of lipid levels and underscores the importance of genetic analyses in understudied populations.

Imaging Genetic Based Mediation Analysis for Human Cognition

The brain connectome maps the structural and functional connectivity that forms an important neurobiological basis for the analysis of human cognitive traits while the genetic predisposition and our cognition ability are frequently found in close association. The issue of how genetic architecture and brain connectome causally affect human behaviors remains unknown. To seek for the potential causal relationship, in this paper, we carried out the causal pathway analysis from single nucleotide polymorphism (SNP) data to four common human cognitive traits, mediated by the brain connectome. Specifically, we selected 942 SNPs that are significantly associated with the brain connectome, and then estimated the direct and indirect effect on the human traits for each SNP. We found out that a majority of the selected SNPs have significant direct effects on human traits and discussed the trait-related brain regions and their implications.

Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease

The study was designed to evaluate putative mechanisms by which lipid-associated loci identified by genome-wide association studies (GWAS) are involved in the molecular pathogenesis of coronary artery disease (CAD) using a comprehensive statistical and bioinformatics analysis. A total of 1700 unrelated individuals of Slavic origin from the Central Russia, including 991 CAD patients and 709 healthy controls were examined. Sixteen lipid-associated GWAS loci were selected from European studies and genotyped using the MassArray-4 system. The polymorphisms were associated with plasma lipids such as total cholesterol (rs12328675, rs4846914, rs55730499, and rs838880), LDL-cholesterol (rs3764261, rs55730499, rs1689800, and rs838880), HDL-cholesterol (rs3764261) as well as carotid intima-media thickness/CIMT (rs12328675, rs11220463, and rs1689800). Polymorphisms such as rs4420638 of APOC1 (p = 0.009), rs55730499 of LPA (p = 0.0007), rs3136441 of F2 (p < 0.0001), and rs6065906 of PLTP (p = 0.002) showed significant associations with the risk of CAD, regardless of sex, age, and body mass index. A majority of the observed associations were successfully replicated in large independent cohorts. Bioinformatics analysis allowed establishing (1) phenotype-specific and shared epistatic gene–gene and gene–smoking interactions contributing to all studied cardiovascular phenotypes; (2) lipid-associated GWAS loci might be allele-specific binding sites for transcription factors from gene regulatory networks controlling multifaceted molecular mechanisms of atherosclerosis.

Sex-specific autosomal genetic effects across 26 human complex traits

Previous studies have shown that men and women have different genetic architectures across many traits. However, except waist-to-hip ratio (WHR) and waist circumference (WC), it remains unknown whether the genetic effects of a certain trait are weaker or stronger on men/women. With ~18 000 Taiwan Biobank subjects, we comprehensively investigate sexual heterogeneity in autosomal genetic effects, for traits regarding cardiovascular health, diabetes, kidney, liver, anthropometric profiles, blood, etc. 'Gene-by-sex interactions' (G $\times$ S) were detected in 18 out of 26 traits, each with an interaction P-value (${{P}}_{{INT}}$) less than $0.05/104={0.00048}$, where 104 is the number of tests conducted in this study. The most significant evidence of G $\times$ S was found in WHR (${{P}}_{{INT}}$ = 3.2 $\times{{10}}^{-{55}}$) and WC (${{P}}_{{INT}}$ = 2.3$\times{{10}}^{-{41}}$). As a novel G$\times$S investigation for other traits, we here find that the autosomal genetic effects are weaker on women than on men, for low-density lipoprotein cholesterol (LDL-C), uric acid (UA) and diabetes-related traits such as fasting glucose and glycated hemoglobin. For LDL-C and UA, the evidence of G$\times$S is especially notable in subjects aged less than 50 years, where estrogen can play a role in attenuating the autosomal genetic effects of these two traits. Men and women have systematically distinct environmental contexts caused by hormonal milieu and their specific society roles, which may trigger diverse gene expressions despite the same DNA materials. As many environmental exposures are difficult to collect and quantify, sex can serve as a good surrogate for these factors.

Genome-wide association studies in Samoans give insight into the genetic architecture of fasting serum lipid levels

The current understanding of the genetic architecture of lipids has largely come from genome-wide association studies (GWAS). To date, few GWAS have examined the genetic architecture of lipids in Polynesians, and none have in Samoans, whose unique population history, including many population bottlenecks, may provide insight into the biological foundations of variation in lipid levels. Here we performed a GWAS of four fasting serum lipid levels: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides (TG) in a sample of 2849 Samoans, with validation genotyping for associations in a replication cohort comprising 1798 Samoans and American Samoans. We identified multiple genome-wide significant associations (P < 5 × 10^-8) previously seen in other populations-APOA1 with TG, CETP with HDL, and APOE with TC and LDL-and several suggestive associations (P < 1 × 10^-5), including an association of variants downstream of MGAT1 and RAB21 with HDL. However, we observed different association signals for variants near APOE than what has been previously reported in non-Polynesian populations. The association with several known lipid loci combined with the newly identified associations with variants near MGAT1 and RAB21 suggest that while some of the genetic architecture of lipids is shared between Samoans and other populations, part of the genetic architecture may be Polynesian-specific.

Re-testing reported significant SNPs related to suicide in a historical high -risk isolated population from north east India

Background

Genetic diathesis of suicide is supported by family and twin studies. Few candidate gene pathways are known, but does not explain fully the complexity of suicide genetic risk. Recent investigations opting for Genome-Wide Association Studies (GWAS) resulted in finding additional targets, but replication remained a challenge. In this respect small isolated population approach in several complex disease phenotypes is found encouraging. The present study is an attempt to re-test some of the reported significant SNPs for suicide among a small historical high- risk isolated population from Northeast India.

Methods

Two hundred ten cases (inclusive of depressed, suicide attempter and depressed + suicide attempter) and 249 controls were considered in the present study which were evaluated for the psychiatric parameters. Sixteen reported significant SNPs for suicide behaviour were re-tested using association approach under various genetic models. Networking by GeneMANIA tool was used for function prediction of the associated genes.

Results

Seven SNPs (of 6 genes) remained significant in different genetic models. On networking genes with significant SNPs IL7, RHEB, CTNN3, KCNIP4, ARFGEF3 are found in interaction with already known candidate gene pathways while SNP rs1109089 (RHEB) gained further support from earlier expression studies. NUGGC gene is in complete isolation.

Conclusions

Small population approach in replicating significant SNPs is useful in complex phenotypes like suicide. This study explored the region-specific demographics of India by identifying vulnerable population for suicide via genetic association analysis in bringing into academic and administrative forum, the importance of suicide as a disease and its biological basis.

The Genetic Basis of Thyroid Function: Novel Findings and New Approaches

CONTEXT

Genetic factors are major determinants of thyroid function. Over the last two decades, multiple genetic variants have been associated with variations in normal range thyroid function tests. Most recently, a large-scale genome-wide association study (GWAS) doubled the number of known variants associated with normal range thyrotropin (TSH) and free thyroxine (FT4) levels.

EVIDENCE ACQUISITION

This review summarizes the results of genetic association studies on normal range thyroid function and explores how these genetic variants can be used in future studies to improve our understanding of thyroid hormone regulation and disease.

EVIDENCE SYNTHESIS

Serum TSH and FT4 levels are determined by multiple genetic variants on virtually all levels of the hypothalamus-pituitary-thyroid (HPT) axis. Functional follow-up studies on top of GWAS hits has the potential to discover new key players in thyroid hormone regulation, as exemplified by the identification of the thyroid hormone transporter SLC17A4 and the metabolizing enzyme AADAT. Translational studies may use these genetic variants to investigate causal associations between thyroid function and various outcomes in Mendelian Randomization (MR) studies, to identify individuals with an increased risk of thyroid dysfunction, and to predict the individual HPT axis setpoint.

CONCLUSIONS

Recent genetic studies have greatly improved our understanding of the genetic basis of thyroid function, and have revealed novel pathways involved in its regulation. In addition, these findings have paved the way for various lines of research that can improve our understanding of thyroid hormone regulation and thyroid diseases, as well as the potential use of these markers in future clinical practice.

Using Genetic Risk Score Approaches to Infer Whether an Environmental Factor Attenuates or Exacerbates the Adverse Influence of a Candidate Gene

Some candidate genes have been robustly reported to be associated with complex traits, such as the fat mass and obesity-associated (FTO) gene on body mass index (BMI), and the fibroblast growth factor 5 (FGF5) gene on blood pressure levels. It is of interest to know whether an environmental factor (E) can attenuate or exacerbate the adverse influence of a candidate gene. To this end, we here evaluate the performance of “genetic risk score” (GRS) approaches to detect “gene-environment interactions” (G × E). In the first stage, a GRS is calculated according to the genotypes of variants in a candidate gene. In the second stage, we test whether E can significantly modify this GRS effect. This two-stage procedure can not only provide a p-value for a G × E test but also guide inferences on how E modifies the adverse effect of a gene. With systematic simulations, we compared several ways to construct a GRS. If E exacerbates the adverse influence of a gene, GRS formed by the elastic net (ENET) or the least absolute shrinkage and selection operator (LASSO) is recommended. However, the performance of ENET or LASSO will be compromised if E attenuates the adverse influence of a gene, and using the ridge regression (RIDGE) can be more powerful in this situation. Applying RIDGE to 18,424 subjects in the Taiwan Biobank, we showed that performing regular exercise can attenuate the adverse influence of the FTO gene on four obesity measures: BMI (p = 0.0009), body fat percentage (p = 0.0031), waist circumference (p = 0.0052), and hip circumference (p = 0.0001). As another example, we used RIDGE and found the FGF5 gene has a stronger effect on blood pressure in Han Chinese with a higher waist-to-hip ratio [p = 0.0013 for diastolic blood pressure (DBP) and p = 0.0027 for systolic blood pressure (SBP)]. This study provides an evaluation on the GRS approaches, which is important to infer whether E attenuates or exacerbates the adverse influence of a candidate gene.

Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

Replicable genetic association signals have consistently been found through genome-wide association studies in recent years. The recent dramatic expansion of study sizes improves power of estimation of effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility of these methods to bias due to subtle population structure. Standard methods using genetic principal components to correct for structure might not always be appropriate and we use a simulation study to illustrate when correction might be ineffective for avoiding biases. New methods such as trans-ethnic modeling and chromosome painting allow for a richer understanding of the relationship between traits and population structure. We illustrate the arguments using real examples (stroke and educational attainment) and provide a more nuanced understanding of population structure, which is set to be revisited as a critical aspect of future analyses in genetic epidemiology. We also make simple recommendations for how problems can be avoided in the future. Our results have particular importance for the implementation of GWAS meta-analysis, for prediction of traits, and for causal inference.

Genetic analysis of hsCRP in American Indians: The Strong Heart Family Study

Background

Increased serum levels of C-reactive protein (CRP), an important component of the innate immune response, are associated with increased risk of cardiovascular disease (CVD). Multiple single nucleotide polymorphisms (SNP) have been identified which are associated with CRP levels, and Mendelian randomization studies have shown a positive association between SNPs increasing CRP expression and risk of colon cancer (but thus far not CVD). The effects of individual genetic variants often interact with the genetic background of a population and hence we sought to resolve the genetic determinants of serum CRP in a number of American Indian populations.

Methods

The Strong Heart Family Study (SHFS) has serum CRP measurements from 2428 tribal members, recruited as large families from three regions of the United States. Microsatellite markers and MetaboChip defined SNP genotypes were incorporated into variance components, decomposition-based linkage and association analyses.

Results

CRP levels exhibited significant heritability (h² = 0.33 ± 0.05, p<1.3 X 10⁻²⁰). A locus on chromosome (chr) 6, near marker D6S281 (approximately at 169.6 Mb, GRCh38/hg38) showed suggestive linkage (LOD = 1.9) to CRP levels. No individual SNPs were found associated with CRP levels after Bonferroni adjustment for multiple testing (threshold <7.77 x 10⁻⁷), however, we found nominal associations, many of which replicate previous findings at the CRP, HNF1A and 7 other loci. In addition, we report association of 46 SNPs located at 7 novel loci on chromosomes 2, 5, 6(2 loci), 9, 10 and 17, with an average of 15.3 Kb between SNPs and all with p-values less than 7.2 X 10⁻⁴.

Conclusion

In agreement with evidence from other populations, these data show CRP serum levels are under considerable genetic influence; and include loci, such as near CRP and other genes, that replicate results from other ethnic groups. These findings also suggest possible novel loci on chr 6 and other chromosomes that warrant further investigation.

Performing different kinds of physical exercise differentially attenuates the genetic effects on obesity measures: Evidence from 18,424 Taiwan Biobank participants

Obesity is a worldwide health problem that is closely linked to many metabolic disorders. Regular physical exercise has been found to attenuate the genetic predisposition to obesity. However, it remains unknown what kinds of exercise can modify the genetic risk of obesity. This study included 18,424 unrelated Han Chinese adults aged 30–70 years who participated in the Taiwan Biobank (TWB). A total of 5 obesity measures were investigated here, including body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). Because there have been no large genome-wide association studies on obesity for Han Chinese, we used the TWB internal weights to construct genetic risk scores (GRSs) for each obesity measure, and then test the significance of GRS-by-exercise interactions. The significance level throughout this work was set at 0.05/550 = 9.1x10^-5 because a total of 550 tests were performed. Performing regular exercise was found to attenuate the genetic effects on 4 obesity measures, including BMI, BFP, WC, and HC. Among the 18 kinds of self-reported regular exercise, 6 mitigated the genetic effects on at least one obesity measure. Regular jogging blunted the genetic effects on BMI, BFP, and HC. Mountain climbing, walking, exercise walking, international standard dancing, and a longer practice of yoga also attenuated the genetic effects on BMI. Exercises such as cycling, stretching exercise, swimming, dance dance revolution, and qigong were not found to modify the genetic effects on any obesity measure. Across all 5 obesity measures, regular jogging consistently presented the most significant interactions with GRSs. Our findings show that the genetic effects on obesity measures can be decreased to various extents by performing different kinds of exercise. The benefits of regular physical exercise are more impactful in subjects who are more predisposed to obesity.

The complex interplay of genetics and lifestyle makes obesity a challenging issue. Previous studies have found performing regular physical exercise could blunt the genetic effects on body mass index (BMI). However, BMI does not take into account lean body mass or identify central obesity. Moreover, it remains unclear what kinds of exercise could more effectively attenuate the genetic effects on obesity measures. With a sample of 18,424 unrelated Han Chinese adults, we comprehensively investigated gene-exercise interactions on 5 obesity measures: BMI, body fat percentage, waist circumference, hip circumference, and waist-to-hip ratio. Moreover, we tested whether the genetic effects on obesity measures could be modified by any of 18 kinds of self-reported regular exercise. Because no large genome-wide association studies on obesity have been done for Han Chinese, we constructed genetic risk scores with internal weights for analyses. Among these exercises, regular jogging consistently presented the strongest evidence to mitigate the genetic effects on all 5 obesity measures. Moreover, mountain climbing, walking, exercise walking, international standard dancing, and a longer practice of yoga attenuated the genetic effects on BMI. The benefits of regularly performing these 6 kinds of exercise are more impactful in subjects who are more predisposed to obesity.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10⁻⁷, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p < 5 × 10⁻⁵). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses.

Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations

OBJECTIVES

Large-scale association studies that mainly involve European populations identified many genetic loci related to high-density lipoprotein cholesterol (HDL-C) levels, one of the most important indicators of the risk for cardiovascular diseases. The question with intense speculation of whether the effect estimates obtained from European populations for different HDL-C level-related SNPs are applicable to the Roma ethnicity, the largest minority group in Europe with a South Asian origin, was addressed in the present study.

DESIGN

The associations between 21 SNPs (in the genes LIPC(G), CETP, GALNT2, HMGCP, ABCA1, KCTD10 and WWOX) and HDL-C levels were examined separately in adults of the Hungarian general (N = 1542) and Roma (N = 646) populations by linear regression. Individual effects (direction and size) of single SNPs on HDL-C levels were computed and compared between the study groups and with data published in the literature.

RESULTS

Significant associations between SNPs and HDL-C levels were more frequently found in general subjects than in Roma subjects (11 SNPs in general vs. 4 SNPs in Roma). The CETP gene variants rs1532624, rs708272 and rs7499892 consistently showed significant associations with HDL-C levels across the study groups (p ˂ 0.05), indicating a possible causal variant(s) in this region. Although nominally significant differences in effect size were found for three SNPs (rs693 in gene APOB, rs9989419 in gene CETP, and rs2548861 in gene WWOX) by comparing the general and Roma populations, most of these SNPs did not have a significant effect on HDL-C levels. The β coefficients for SNPs in the Roma population were found to be identical both in direction and magnitude to the effect obtained previously in large-scale studies on European populations.

CONCLUSIONS

The effect of the vast majority of the SNPs on HDL-C levels could be replicated in the Hungarian general and Roma populations, which indicates that the effect size measurements obtained from the literature can be used for risk estimation for both populations.

AMPK activation negatively regulates GDAP1, which influences metabolic processes and circadian gene expression in skeletal muscle

Objective

We sought to identify AMPK-regulated genes via bioinformatic analysis of microarray data generated from skeletal muscle of animal models with genetically altered AMPK activity. We hypothesized that such genes would play a role in metabolism. Ganglioside-induced differentiation-associated protein 1 (GDAP1), a gene which plays a role in mitochondrial fission and peroxisomal function in neuronal cells but whose function in skeletal muscle is undescribed, was identified and further validated. AMPK activation reduced GDAP1 expression in skeletal muscle. GDAP1 expression was elevated in skeletal muscle from type 2 diabetic patients but decreased after acute exercise.

Methods

The metabolic impact of GDAP1 silencing was determined in primary skeletal muscle cells via siRNA-transfections. Confocal microscopy was used to visualize whether silencing GDAP1 impacted mitochondrial network morphology and membrane potential.

Results

GDAP1 silencing increased mitochondrial protein abundance, decreased palmitate oxidation, and decreased non-mitochondrial respiration. Mitochondrial morphology was unaltered by GDAP1 silencing. GDAP1 silencing and treatment of cells with AMPK agonists altered several genes in the core molecular clock machinery.

Conclusion

We describe a role for GDAP1 in regulating mitochondrial proteins, circadian genes, and metabolic flux in skeletal muscle. Collectively, our results implicate GDAP1 in the circadian control of metabolism.

•

Transcriptomic studies reveal GDAP1 mRNA is inversely associated with AMPK activity.

•

GDAP1 silencing increases mitochondrial protein abundance in skeletal muscle.

•

GDAP1 silencing influences expression of core molecular clock machinery.

•

GDAP1 is a AMPK target involved in metabolism and circadian gene expression.

Quantitative analysis of population-scale family trees with millions of relatives

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource.

Genetic architecture: the shape of the genetic contribution to human traits and disease

Genetic architecture describes the characteristics of genetic variation that are responsible for heritable phenotypic variability. It depends on the number of genetic variants affecting a trait, their frequencies in the population, the magnitude of their effects and their interactions with each other and the environment. Defining the genetic architecture of a complex trait or disease is central to the scientific and clinical goals of human genetics, which are to understand disease aetiology and aid in disease screening, diagnosis, prognosis and therapy. Recent technological advances have enabled genome-wide association studies and emerging next-generation sequencing studies to begin to decipher the nature of the heritable contribution to traits and disease. Here, we describe the types of genetic architecture that have been observed, how architecture can be measured and why an improved understanding of genetic architecture is central to future advances in the field.

Relationship between Lipid Phenotypes, Overweight, Lipid Lowering Drug Response and KIF6 and HMG-CoA Genotypes in a Subset of the Brisighella Heart Study Population

The existence of genetic traits might explain the susceptibility to develop hypercholesterolemia and the inter-individual differences in statin response. This study was performed to evaluate whether individuals' polymorphisms in HMG-CoA and KIF6 genes are independently associated with hypercholesterolemia, other lipid-associated traits, and statin response in unselected individuals enrolled in the Brisighella heart study (Survey 2012). A total of 1622 individuals, of which 183 under statin medication, were genotyped for a total of five polymorphisms (KIF6 rs20455, rs9471077, rs9462535; HMG-CoA rs3761740, rs3846662). The relationships between the five loci and clinical characteristics were analyzed. The principal basic parameters calculated on 12 h fasting blood included total cholesterol (TC), High Density Lipoprotein Cholesterol (HDL-C), Low-Density Lipoprotein Cholesterol (LDL-C), and triglycerides (TG). Hypercholesterolemia was defined as a TC >200 mg/dL or use of lipid-lowering medication. 965 individuals were characterized by hypercholesterolemia; these subjects were significantly older (p < 0.001), with body mass index (BMI) and waist circumference significantly higher (p < 0.001) compared to the others. HMG-CoA rs3846662 GG genotype was significantly over-represented in the hypercholesterolemic group (p = 0.030). HMG-CoA rs3846662 genotype was associated with the level of TC and LDL-C. Furthermore, in the same subset of untreated subjects, we observed a significant correlation between the KIF6 rs20455 and HDL-C. KIF6 variants were associated with a significantly lower (rs20455) or higher (rs9471077 and rs9462535) risk of obesity, in males only. No association between responsiveness to statins and the polymorphisms under investigation were observed. Our results showed associations between HMG-CoA rs3846662 and KIF6 rs20455 and lipid phenotypes, which may have an influence on dyslipidemia-related events. Moreover, this represents the first study implicating KIF6 variants with obesity in men, and point to the possible involvement of this genetic locus in the known gender-related differences in coronary artery disease.

Association of SCN10A Polymorphisms with the Recurrence of Atrial Fibrillation after Catheter Ablation in a Chinese Han Population

The nonsynonymous SCN10A single nucleotide polymorphism (SNP) rs6795970 has been reported to associate with PR interval and atrial fibrillation (AF) and in strong linkage disequilibrium (LD) with the AF-associated SNP rs6800541. In this study, we investigated whether rs6795970 polymorphisms are associated with AF recurrence after catheter ablation. A total of 502 consecutive patients with AF who underwent catheter ablation were included. AF recurrence was defined as a documented episode of any atrial arrhythmias lasting ≥30 s after a blanking period of 3 months. AF recurrence was observed between 3 and 12 months after catheter ablation in 24.5% of the patients. There was a significant difference in the allele distribution (p = 7.86 × 10⁻⁵) and genotype distribution (p = 1.42 × 10⁻⁵) of rs6795970 between the AF recurrence and no recurrence groups. In a multivariate analysis, we identified the following independent predictors of AF recurrence: the rs6795970 genotypes in an additive model (OR 0.36, 95%CI 0.22~0.60, p = 7.04 × 10⁻⁵), a history of AF ≥36 months (OR 3.57, 95%CI 2.26~5.63, p = 4.33 × 10⁻⁸) and left atrial diameter (LAD) ≥40 mm (OR 1.85, 95%CI 1.08~3.19, p = 0.026). These data suggest that genetic variation in SCN10A may play an important role in predicting AF recurrence after catheter ablation in the Chinese Han population.

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.

Multiple susceptibility loci at chromosome 11q23.3 are associated with plasma triglyceride in East Asians

Genetic studies of plasma TG levels have identified associations with multiple candidate loci on chromosome11q23.3, which harbors a number of genes, including BUD13, ZNF259, and APOA5-A4-C3-A1. This study aimed to examine whether these multiple candidate genes on the 11q23.3 regions exert independent effects on TG levels or whether their effects are confounded by linkage disequilibrium (LD). We performed a genome-wide association study and consequent fine-mapping analyses on TG levels in two Korean population-based cohorts: the Korea Association Resource study (n = 8,223) and the Healthy Twin study (n = 1,735). A total of 301 loci reached genome-wide significance level in pooled analysis, including 10 SNPs with weak LD (r(2) < 0.06) clustered on 11q23.3: ApoA5 (rs651821, rs2075291); ZNF259 (rs964184, rs603446); BUD13 (rs11216126); Apoa4 (rs7396851); SIK3 (rs12292858); PCSK7 (rs199890178); PAFAH1B2 (rs12420127), and SIDT2 (rs2269399). When the inter-dependence between alleles was examined using conditional models, five loci on BUD13, ZNF259, and ApoA5 showed possible independent associations. A haplotype analysis using five SNPs revealed both hyper- and hypotriglyceridemic haplotypes, which are relatively common in Koreans (haplotype frequency 0.08-0.22). Our findings suggest the presence of multiple functional loci on 11q23.3, which might exert their effects on plasma TG level independently or through complex interactions between functional loci.

A Phenomic Scan of the Norfolk Island Genetic Isolate Identifies a Major Pleiotropic Effect Locus Associated with Metabolic and Renal Disorder Markers

Multiphenotype genome-wide association studies (GWAS) may reveal pleiotropic genes, which would remain undetected using single phenotype analyses. Analysis of large pedigrees offers the added advantage of more accurately assessing trait heritability, which can help prioritise genetically influenced phenotypes for GWAS analysis. In this study we performed a principal component analysis (PCA), heritability (h²) estimation and pedigree-based GWAS of 37 cardiovascular disease -related phenotypes in 330 related individuals forming a large pedigree from the Norfolk Island genetic isolate. PCA revealed 13 components explaining >75% of the total variance. Nine components yielded statistically significant h² values ranging from 0.22 to 0.54 (P<0.05). The most heritable component was loaded with 7 phenotypic measures reflecting metabolic and renal dysfunction. A GWAS of this composite phenotype revealed statistically significant associations for 3 adjacent SNPs on chromosome 1p22.2 (P<1x10^-8). These SNPs form a 42kb haplotype block and explain 11% of the genetic variance for this renal function phenotype. Replication analysis of the tagging SNP (rs1396315) in an independent US cohort supports the association (P = 0.000011). Blood transcript analysis showed 35 genes were associated with rs1396315 (P<0.05). Gene set enrichment analysis of these genes revealed the most enriched pathway was purine metabolism (P = 0.0015). Overall, our findings provide convincing evidence for a major pleiotropic effect locus on chromosome 1p22.2 influencing risk of renal dysfunction via purine metabolism pathways in the Norfolk Island population. Further studies are now warranted to interrogate the functional relevance of this locus in terms of renal pathology and cardiovascular disease risk.

While many large genetic association studies have identified genes playing a role in complex disorders, there is still concern over the amount of missing genetic heritability. With this in mind, we have used a data reduction approach alongside pedigree-based association to obtain highly heritable components which explain 'hidden' variance of multiphenotypes within a large pedigree from the Norfolk Island genetic isolate. The most heritable of these components involved 7 traits reflecting metabolic and renal functionality, association of which locates to an intergenic region on chromosome 1p22.2. By integrating gene expression information, we identified enrichment of a purine metabolism pathway, further strengthening the metabolic nature of the observed association. Adding additional support to our approach, we show association of the tagging SNP (rs1396315) in an independent US population. The findings presented here are of particular interest as they implicate pleiotropic effect loci and newly associated biological pathways underlying cardiovascular disease risk.

Pacific Populations, Metabolic Disease and 'Just-So Stories': A Critique of the 'Thrifty Genotype' Hypothesis in Oceania

Pacific populations have long been observed to suffer a high burden of metabolic disease, including obesity, type 2 diabetes and gout. The 'Thrifty Genotype' hypothesis has frequently been used to explain this high prevalence of disease. Here, the 'Thrifty Genotype' hypothesis and the evolutionary background of Pacific populations are examined. We question its relevance not only in the Pacific region but more generally. Not only has the hypothesis not been explicitly tested, but most archaeological and anthropological data from the Pacific fundamentally do not support its application.

Comparative Analyses of QTLs Influencing Obesity and Metabolic Phenotypes in Pigs and Humans

The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genome-wide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.

A single nucleotide polymorphism associated with isolated cleft lip and palate, thyroid cancer and hypothyroidism alters the activity of an oral epithelium and thyroid enhancer near FOXE1

Three common diseases, isolated cleft lip and cleft palate (CLP), hypothyroidism and thyroid cancer all map to the FOXE1 locus, but causative variants have yet to be identified. In patients with CLP, the frequency of coding mutations in FOXE1 fails to account for the risk attributable to this locus, suggesting that the common risk alleles reside in nearby regulatory elements. Using a combination of zebrafish and mouse transgenesis, we screened 15 conserved non-coding sequences for enhancer activity, identifying three that regulate expression in a tissue specific pattern consistent with endogenous foxe1 expression. These three, located -82.4, -67.7 and +22.6 kb from the FOXE1 start codon, are all active in the oral epithelium or branchial arches. The -67.7 and +22.6 kb elements are also active in the developing heart, and the -67.7 kb element uniquely directs expression in the developing thyroid. Within the -67.7 kb element is the SNP rs7850258 that is associated with all three diseases. Quantitative reporter assays in oral epithelial and thyroid cell lines show that the rs7850258 allele (G) associated with CLP and hypothyroidism has significantly greater enhancer activity than the allele associated with thyroid cancer (A). Moreover, consistent with predicted transcription factor binding differences, the -67.7 kb element containing rs7850258 allele G is significantly more responsive to both MYC and ARNT than allele A. By demonstrating that this common non-coding variant alters FOXE1 expression, we have identified at least in part the functional basis for the genetic risk of these seemingly disparate disorders.

The association of MC4R rs17782313 polymorphism with dietary intake in Iranian adults

BACKGROUND

Malfunction in the energy homeostasis system is a major cause of developing obesity. Melanocortin-4 receptor (MC4R) plays a crucial role in this system as a key receptor. Although MC4R gene as an obesity candidate gene is associated with higher BMI, only few attempts have been carried out to understand the mechanism underlying body-weight regulation.

OBJECTIVE

The aim of this study is to investigate the association between variant rs17782313 near MC4R gene and both dietary energy and macronutrient intakes.

METHODS

An Iranian population, 400 adults aged over 22years were selected from the Iranian Multicenter Osteoporosis Study (IMOS). Genotyping for the near MC4R rs17782313 was performed by PCR-RFLP. Weight and height were measured. Dietary intake and physical activity were assessed by using validated questionnaires. Analysis was carried out in two groups with regard to BMI. Multiple linear regression models adjusted for covariates were used to examine the association between rs17782313 and dietary intake.

RESULTS

MC4R rs17782313 was associated with high energy intake (P<0.001), and low carbohydrate and protein intakes (P<0.001 and P<0.01 respectively). In addition, the significant association between variant rs17782313 and fat intake disappeared after adjusting for energy.

CONCLUSIONS

The rs17782313 variant contributes to the variety of dietary energy and energy-dense macronutrient intakes. Moreover, a novel association was suggested between this polymorphism and dietary fat intake.

An integrated approach to defining genetic and environmental determinants for major clinical outcomes involving vitamin D

There is substantial genetic and epidemiological evidence implicating vitamin D in the pathogenesis of many common diseases. A number of studies have sought to define an association for disease with sequence variation in the VDR gene, encoding the ligand-activated nuclear hormone receptor for vitamin D. The results of such studies have been difficult to replicate and are likely to need to account for specific environmental exposures. Here, we review recent work that has begun to study the interactions between VDR gene polymorphisms, vitamin D blood levels, and complex disease susceptibility, notably in the context of major clinical outcomes. We highlight the challenges moving forward in this area and its importance for effective clinical translation of current research.

Genome-wide admixture and association study of serum iron, ferritin, transferrin saturation and total iron binding capacity in African Americans

Iron is an essential component of many important proteins and enzymes, including hemoglobin, which is responsible for carrying oxygen to the cells. African Americans (AAs) have a greater prevalence of iron deficiency compared with European Americans. We conducted genome-wide admixture-mapping and association studies for serum iron, serum ferritin, transferrin saturation (SAT) and total iron binding capacity (TIBC) in 2347 AAs participating in the Jackson Heart Study (JHS). Follow-up replication analyses for JHS iron-trait associated SNPs were conducted in 329 AA participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study (HANDLS). Higher estimated proportions of global African ancestry were significantly associated with lower levels of iron (P = 2.4 × 10(-5)), SAT (P = 0.0019) and TIBC (P = 0.042). We observed significant associations (P < 5 × 10(-8)) between serum TIBC levels and two independent SNPs around TF on chromosome 3, the first report of a genome-wide significant second independent signal in this region, and SNPs near two novel genes: HDGFL1 on chromosome 6 and MAF on chromosome 16. We also observed significant associations between ferritin levels and SNPs near GAB3 on chromosome X. We replicated our two independent associations at TF and our association at GAB3 in HANDLS. Our study provides evidence for both shared and unique genetic risk factors that are associated with iron-related measures in AAs. The top two variants in TF explain 11.2% of the total variation in TIBC levels in AAs after accounting for age, gender, body mass index and background ancestry.

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

A genome-wide association study on thyroid function and anti-thyroid peroxidase antibodies in Koreans

Genetic factors are thought to be an important determinant of thyroid function and autoimmunity. However, there are limited data on genetic variants in Asians. In this study, we performed a genome-wide association study on plasma thyroid-stimulating hormone (TSH) and free thyroxine (fT4) concentration and anti-thyroid peroxidase (anti-TPO) antibody positivity in 4238 Korean subjects. In the Stage 1 genome scan, 3396 participants from the Ansung cohort were investigated using 1.42 million genotyped or imputed markers. In the Stage 2 follow-up, 10 markers were genotyped in 842 participants from the Korean Longitudinal Study on Health and Aging cohort. An intronic variant in VAV3, rs12126655, which has been reported in Europeans, was significantly associated with plasma TSH concentration in the joint Stages 1 and 2 analyses (P = 2.2 × 10(-8)). We observed that a novel variant, rs2071403, located 75 bp proximal to the translational start site of TPO was significantly associated with plasma anti-TPO antibody positivity in the joint Stages 1 and 2 analyses (P = 1.3 × 10(-10)). This variant had a marginal sex-specific effect, and its association was more significant in females. Subjects possessing the rs2071403A allele, associated with an absence of the anti-TPO antibody, had decreased TPO mRNA expression in their thyroid tissue. Another intronic variant of HLA-DPB2, rs733208, had a suggestive association with anti-TPO antibody positivity (P = 4.2 × 10(-7)). In conclusion, we have identified genetic variants that are strongly associated with TSH level and anti-TPO antibody positivity in Koreans. Further replications and meta-analysis are required to confirm these findings.

The Saguenay-Lac-Saint-Jean asthma familial collection: the genetics of asthma in a young founder population

To study the genetics of asthma, a familial collection was built in the Saguenay-Lac-Saint-Jean (SLSJ) region, which is localized in northeastern Quebec, Canada, and which is characterized by a young founder effect. Recruitment was performed through probands with a specific asthma phenotype. The collection includes 1394 individuals distributed in 271 families. A phenotypic profile including more than 75 phenotypic characteristics was defined for each participant using a standardized questionnaire, respiratory measures and allergic tests. A genome-wide association study on 1214 of these samples for asthma-related phenotypes (asthma, atopy and rhinitis) and for white blood cell types was performed. These analyses allowed associating 10 single nucleotide polymorphisms (SNPs) with P<1 × 10(-5) with asthma-related phenotypes and 11 SNPs with white blood cell counts. Among them, four SNPs are located in or near genes with functions related to asthma or allergy. Moreover, several loci were identified as 5q31.1 that includes 22 SNPs associated with atopy (P<1 × 10(-3)) and located near a cytokine cluster, and 17q21.2 with seven SNPs associated with asthma. This study highlights the value of a familial collection with a fine phenotypic description and characterized by a young founder effect in the search of the genetic determinants involved in complex traits such as asthma.

Who are the Okinawans? Ancestry, genome diversity, and implications for the genetic study of human longevity from a geographically isolated population

Isolated populations have advantages for genetic studies of longevity from decreased haplotype diversity and long-range linkage disequilibrium. This permits smaller sample sizes without loss of power, among other utilities. Little is known about the genome of the Okinawans, a potential population isolate, recognized for longevity. Therefore, we assessed genetic diversity, structure, and admixture in Okinawans, and compared this with Caucasians, Chinese, Japanese, and Africans from HapMap II, genotyped on the same Affymetrix GeneChip Human Mapping 500K array. Principal component analysis, haplotype coverage, and linkage disequilibrium decay revealed a distinct Okinawan genome-more homogeneity, less haplotype diversity, and longer range linkage disequilibrium. Population structure and admixture analyses utilizing 52 global reference populations from the Human Genome Diversity Cell Line Panel demonstrated that Okinawans clustered almost exclusively with East Asians. Sibling relative risk (λs) analysis revealed that siblings of Okinawan centenarians have 3.11 times (females) and 3.77 times (males) more likelihood of centenarianism. These findings suggest that Okinawans are genetically distinct and share several characteristics of a population isolate, which are prone to develop extreme phenotypes (eg, longevity) from genetic drift, natural selection, and population bottlenecks. These data support further exploration of genetic influence on longevity in the Okinawans.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Centenarians as super-controls to assess the biological relevance of genetic risk factors for common age-related diseases: a proof of principle on type 2 diabetes

Genetic association studies of age-related, chronic human diseases often suffer from a lack of power to detect modest effects. Here we propose an alternative approach of including healthy centenarians as a more homogeneous and extreme control group. As a proof of principle we focused on type 2 diabetes (T2D) and assessed allelic/genotypic associations of 31 SNPs associated with T2D, diabetes complications and metabolic diseases and SNPs of genes relevant for telomere stability and age-related diseases. We hypothesized that the frequencies of risk variants are inversely correlated with decreasing health and longevity. We performed association analyses comparing diabetic patients and non-diabetic controls followed by association analyses with extreme phenotypic groups (T2D patients with complications and centenarians). Results drew attention to rs7903146 (TCF7L2 gene) that showed a constant increase in the frequencies of risk genotype (TT) from centenarians to diabetic patients who developed macro-complications and the strongest genotypic association was detected when diabetic patients were compared to centenarians (p_value = 9.066*10⁻⁷). We conclude that robust and biologically relevant associations can be obtained when extreme phenotypes, even with a small sample size, are compared.

Longitudinal study shows increasing obesity and hyperglycemia in micronesia

OBJECTIVE

Obesity and diabetes are particularly high in indigenous populations exposed to a Western diet and lifestyle. The prevalence of obesity, diabetes, hyperglycemia, dyslipidemia, and hypertension in one such population, the Micronesian island of Kosrae was described.

DESIGN AND METHODS

Longitudinal screenings for metabolic traits were conducted on adult Kosraens ≥ 20 years of age in 1994 and again in 2001. Data was obtained on 3,106 Kosraens, comprising ∼80% of the adult population. Diabetes was diagnosed using World Health Organization guidelines. Prevalences of obesity, hyperglycemia, dyslipidemia, and hypertension were assessed.

RESULTS

The overall age-adjusted prevalence of diabetes increased from 14 to 21%. The most significant change observed in the population was increases in obesity and hyperglycemia, especially among young Kosraens and women. Obesity age-adjusted prevalence increased from 45 to 62%, and hyperglycemia age-adjusted prevalence increased from 19 to 44%. Of note, Kosraens as a group had unusually low high density lipoprotein (HDL) levels with 80% classified as low HDL by NCEP-ATPIII criteria, despite lacking the usually accompanying increase in triglycerides. Comparison to reports from other populations shows that Kosrae experiences one of the highest rates of obesity, hyperglycemia, and low HDL globally while maintaining relatively healthy levels of triglycerides.

CONCLUSION

Our study shows a dramatic increase in obesity and hyperglycemia in Kosrae in just 7 years and forebodes significantly increased health risks for this part of the world.

Hypertension and genetic variation in endothelial-specific genes

Genome-wide association (GWA) studies usually detect common genetic variants with low-to-medium effect sizes. Many contributing variants are not revealed, since they fail to reach significance after strong correction for multiple comparisons. The WTCCC study for hypertension, for example, failed to identify genome-wide significant associations. We hypothesized that genetic variation in genes expressed specifically in the endothelium may be important for hypertension development. Results from the WTCCC study were combined with previously published gene expression data from mice to specifically investigate SNPs located within endothelial-specific genes, bypassing the requirement for genome-wide significance. Six SNPs from the WTCCC study were selected for independent replication in 5205 hypertensive patients and 5320 population-based controls, and successively in a cohort of 16537 individuals. A common variant (rs10860812) in the DRAM (damage-regulated autophagy modulator) locus showed association with hypertension (P = 0.008) in the replication study. The minor allele (A) had a protective effect (OR = 0.93; 95% CI 0.88–0.98 per A-allele), which replicates the association in the WTCCC GWA study. However, a second follow-up, in the larger cohort, failed to reveal an association with blood pressure. We further tested the endothelial-specific genes for co-localization with a panel of newly discovered SNPs from large meta-GWAS on hypertension or blood pressure. There was no significant overlap between those genes and hypertension or blood pressure loci. The result does not support the hypothesis that genetic variation in genes expressed in endothelium plays an important role for hypertension development. Moreover, the discordant association of rs10860812 with blood pressure in the case control study versus the larger Malmö Preventive Project–study highlights the importance of rigorous replication in multiple large independent studies.

A proximity-based method to identify genomic regions correlated with a continuously varying environmental variable

Knowledge of markers in the human genome which show spatial patterns and display extreme correlation with different environmental determinants play an important role in understanding the factors which affect the biological evolution of our species. We used the genotype data of more than half a million single nucleotide polymorphisms (SNPs) from the data set Human Genome Diversity Panel (HGDP-CEPH -CEPH) and we calculated Spearman's correlation between absolute latitude and one of the two allele frequencies of each SNP. We selected SNPs with a correlation coefficient within the upper 1% tail of the distribution. We then used a criterion of proximity between significant variants to focus on DNA regions showing a continuous signal over a portion of the genome. Based on external information and genome annotations, we demonstrated that most regions with the strongest signals also have biological relevance. We believe this proximity requirement adds an edge to our novel method compared to the existing literature, highlighting several genes (for example DTNB, DOT1L, TPCN2, RELN, MSRA, NRG3) related to body size or shape, human height, hair color, and schizophrenia. Our approach can be applied generally to any measure of association between polymorphic frequencies and continuously varying environmental variables.

Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank

Background

The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form “biobanks” where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on a large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypotheses generation.

Results

In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped for Type 2 Diabetes and Hypothyroidism to discover gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries.

Conclusions

This study demonstrates how Semantic Web technologies can be applied in conjunction with clinical data stored in EHRs to accurately identify subjects with specific diseases and phenotypes, and identify genotype-phenotype associations.

Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population

Genetic variants responsible for susceptibility to obesity and its comorbidities among Hispanic children have not been identified. The VIVA LA FAMILIA Study was designed to genetically map childhood obesity and associated biological processes in the Hispanic population. A genome-wide association study (GWAS) entailed genotyping 1.1 million single nucleotide polymorphisms (SNPs) using the Illumina Infinium technology in 815 children. Measured genotype analysis was performed between genetic markers and obesity-related traits i.e., anthropometry, body composition, growth, metabolites, hormones, inflammation, diet, energy expenditure, substrate utilization and physical activity. Identified genome-wide significant loci: 1) corroborated genes implicated in other studies (MTNR1B, ZNF259/APOA5, XPA/FOXE1 (TTF-2), DARC, CCR3, ABO); 2) localized novel genes in plausible biological pathways (PCSK2, ARHGAP11A, CHRNA3); and 3) revealed novel genes with unknown function in obesity pathogenesis (MATK, COL4A1). Salient findings include a nonsynonymous SNP (rs1056513) in INADL (p = 1.2E-07) for weight; an intronic variant in MTNR1B associated with fasting glucose (p = 3.7E-08); variants in the APOA5-ZNF259 region associated with triglycerides (p = 2.5-4.8E-08); an intronic variant in PCSK2 associated with total antioxidants (p = 7.6E-08); a block of 23 SNPs in XPA/FOXE1 (TTF-2) associated with serum TSH (p = 5.5E-08 to 1.0E-09); a nonsynonymous SNP (p = 1.3E-21), an intronic SNP (p = 3.6E-13) in DARC identified for MCP-1; an intronic variant in ARHGAP11A associated with sleep duration (p = 5.0E-08); and, after adjusting for body weight, variants in MATK for total energy expenditure (p = 2.7E-08) and in CHRNA3 for sleeping energy expenditure (p = 6.0E-08). Unprecedented phenotyping and high-density SNP genotyping enabled localization of novel genetic loci associated with the pathophysiology of childhood obesity.

Murine gut microbiota is defined by host genetics and modulates variation of metabolic traits

The gastrointestinal tract harbors a complex and diverse microbiota that has an important role in host metabolism. Microbial diversity is influenced by a combination of environmental and host genetic factors and is associated with several polygenic diseases. In this study we combined next-generation sequencing, genetic mapping, and a set of physiological traits of the BXD mouse population to explore genetic factors that explain differences in gut microbiota and its impact on metabolic traits. Molecular profiling of the gut microbiota revealed important quantitative differences in microbial composition among BXD strains. These differences in gut microbial composition are influenced by host-genetics, which is complex and involves many loci. Linkage analysis defined Quantitative Trait Loci (QTLs) restricted to a particular taxon, branch or that influenced the variation of taxa across phyla. Gene expression within the gastrointestinal tract and sequence analysis of the parental genomes in the QTL regions uncovered candidate genes with potential to alter gut immunological profiles and impact the balance between gut microbial communities. A QTL region on Chr 4 that overlaps several interferon genes modulates the population of Bacteroides, and potentially Bacteroidetes and Firmicutes–the predominant BXD gut phyla. Irak4, a signaling molecule in the Toll-like receptor pathways is a candidate for the QTL on Chr15 that modulates Rikenellaceae, whereas Tgfb3, a cytokine modulating the barrier function of the intestine and tolerance to commensal bacteria, overlaps a QTL on Chr 12 that influence Prevotellaceae. Relationships between gut microflora, morphological and metabolic traits were uncovered, some potentially a result of common genetic sources of variation.