Genome-wide association study identifies novel loci association with fasting insulin and insulin resistance in African Americans

Sex and Race Differences in Obesity-Related Genetic Susceptibility and Risk of Cardiometabolic Disease in Older US Adults

Importance

The fat mass and obesity-associated gene (FTO) is associated with obesity phenotypes, but the association is inconsistent across populations. Within-population differences may explain some of the variability observed.

Objective

To investigate sex differences in the association between FTO single-nucleotide variants (SNVs) and obesity traits among self-identified non-Hispanic Black and non-Hispanic White US adults, to examine whether the SNVs were associated with cardiometabolic diseases, and to evaluate whether obesity mediated the association between FTO SNVs and cardiometabolic diseases.

Design, Setting, and Participants

This cross-sectional study used data from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a US population-based cohort study with available genetic data (assayed in 2018) and phenotypic data at baseline (enrolled 2003-2007). Participants were aged 45 to 98 years at baseline. Data were analyzed from October 2021 to October 2022.

Exposures

Eleven SNVs in the FTO gene present among both Black and White participants.

Main Outcomes and Measures

Objectively measured obesity indicators (body mass index and waist-to-height ratio), objectively measured and/or self-reported cardiometabolic diseases (hypertension, stroke history, heart disease, and diabetes), and self-reported social-economic and psychosocial status.

Results

A total of 10 447 participants (mean [SD] age, 64.4 [9.7] years; 5276 [55.8%] women; 8743 [83.7%] Black and 1704 [16.3%] White) were included. In the White group, 11 FTO SNVs were significantly associated with obesity, hypertension, and diabetes using linear models (eg, body mass index: β = 0.536; 95% CI, 0.197-0.875), but none of the FTO SNVs were associated with obesity traits in the Black group. White males had a higher risk of obesity while White females had a higher risk of hypertension and diabetes. However, 1 FTO SNV (rs1121980) was associated with a direct increase in the risk of heart disease in Black participants not mediated by obesity (c' = 0.145 [SE, 0.0517]; P = .01).

Conclusions and Relevance

In this cross-sectional study of obesity phenotypes and their association with cardiometabolic diseases, the tested FTO SNVs reflected sex differences in White participants. Different patterns of associations were observed among self-identified Black participants. Therefore, these results could inform future work discovering risk alleles or risk scores unique to Black individuals or further investigating genetic risk in all US residents.

Dimensionality reduction approach for many-objective epistasis analysis

In epistasis analysis, single-nucleotide polymorphism-single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e. binary traits), the score for model quality is affected by different objective functions (i.e. measurements) because of potential disease model preferences and disease complexities. Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. However, SSI identification using MOMDR remains a challenge because the optimal measure combination of objective functions has yet to be investigated. This study extended MOMDR to the many-objective version (i.e. many-objective MDR, MaODR) by integrating various disease probability measures based on a two-way contingency table to improve the identification of SSI between cases and controls. We introduced an objective function selection approach to determine the optimal measure combination in MaODR among 10 well-known measures. In total, 6 disease models with and 40 disease models without marginal effects were used to evaluate the general algorithms, namely those based on multifactor dimensionality reduction, MOMDR and MaODR. Our results revealed that the MaODR-based three objective function model, correct classification rate, likelihood ratio and normalized mutual information (MaODR-CLN) exhibited the higher 6.47% detection success rates (Accuracy) than MOMDR and higher 17.23% detection success rates than MDR through the application of an objective function selection approach. In a Wellcome Trust Case Control Consortium, MaODR-CLN successfully identified the significant SSIs (P < 0.001) associated with coronary artery disease. We performed a systematic analysis to identify the optimal measure combination in MaODR among 10 objective functions. Our combination detected SSIs-based binary traits with weak marginal effects and thus reduced spurious variables in the score model. MOAI is freely available at https://sites.google.com/view/maodr/home.

The molecular phenotype of kisspeptin neurons in the medial amygdala of female mice

Reproduction is regulated through the hypothalamic-pituitary-gonadal (HPG) axis, largely via the action of kisspeptin neurons in the hypothalamus. Importantly, Kiss1 neurons have been identified in other brain regions, including the medial amygdala (MeA). Though the MeA is implicated in regulating aspects of both reproductive physiology and behavior, as well as non-reproductive processes, the functional roles of MeA Kiss1 neurons are largely unknown. Additionally, besides their stimulation by estrogen, little is known about how MeA Kiss1 neurons are regulated. Using a RiboTag mouse model in conjunction with RNA-seq, we examined the molecular profile of MeA Kiss1 neurons to identify transcripts that are co-expressed in MeA Kiss1 neurons of female mice and whether these transcripts are modulated by estradiol (E₂) treatment. RNA-seq identified >13,800 gene transcripts co-expressed in female MeA Kiss1 neurons, including genes for neuropeptides and receptors implicated in reproduction, metabolism, and other neuroendocrine functions. Of the >13,800 genes co-expressed in MeA Kiss1 neurons, only 45 genes demonstrated significantly different expression levels due to E₂ treatment. Gene transcripts such as Kiss1, Gal, and Oxtr increased in response to E₂ treatment, while fewer transcripts, such as Esr1 and Cyp26b1, were downregulated by E₂. Dual RNAscope and immunohistochemistry was performed to validate co-expression of MeA Kiss1 with Cck and Cartpt. These results are the first to establish a profile of genes actively expressed by MeA Kiss1 neurons, including a subset of genes regulated by E₂, which provides a useful foundation for future investigations into the regulation and function of MeA Kiss1 neurons.

Adipocyte-Specific Modulation of KLF14 Expression in Mice Leads to Sex-Dependent Impacts on Adiposity and Lipid Metabolism

Genome-wide association studies identified single nucleotide polymorphisms on chromosome 7 upstream of KLF14 to be associated with metabolic syndrome traits and increased risk for type 2 diabetes (T2D). The associations were more significant in women than in men. The risk allele carriers expressed lower levels of the transcription factor KLF14 in adipose tissues than nonrisk allele carriers. To investigate how adipocyte KLF14 regulates metabolic traits in a sex-dependent manner, we characterized high-fat diet-fed male and female mice with adipocyte-specific Klf14 deletion or overexpression. Klf14 deletion resulted in increased fat mass in female mice and decreased fat mass in male mice. Female Klf14-deficient mice had overall smaller adipocytes in subcutaneous fat depots but larger adipocytes in parametrial depots, indicating a shift in lipid storage from subcutaneous to visceral fat depots. They had reduced metabolic rates and increased respiratory exchange ratios consistent with increased use of carbohydrates as an energy source. Fasting- and isoproterenol-induced adipocyte lipolysis was defective in female Klf14-deficient mice, and concomitantly, adipocyte triglycerides lipase mRNA levels were downregulated. Female Klf14-deficient mice cleared blood triglyceride and nonesterified fatty acid less efficiently than wild-type. Finally, adipocyte-specific overexpression of Klf14 resulted in lower total body fat in female but not male mice. Taken together, consistent with human studies, adipocyte KLF14 deficiency in female but not in male mice causes increased adiposity and redistribution of lipid storage from subcutaneous to visceral adipose tissues. Increasing KLF14 abundance in adipocytes of females with obesity and T2D may provide a novel treatment option to alleviate metabolic abnormalities.

An update of the consensus statement on insulin resistance in children 2010

In our modern society, where highly palatable and calorie-rich foods are readily available, and sedentary lifestyle is common among children and adolescents, we face the pandemic of obesity, nonalcoholic fatty liver disease, hypertension, atherosclerosis, and T2D. Insulin resistance (IR) is known to be the main underlying mechanism of all these associated health consequences; therefore, the early detection of IR is fundamental for preventing them.A Consensus Statement, internationally supported by all the major scientific societies in pediatric endocrinology, was published in 2010, providing all the most recent reliable evidence to identify the definition of IR in children, its measurement, its risk factors, and the effective strategies to prevent and treat it. However, the 2010 Consensus concluded that further research was necessary to assess some of the discussed points, in particular the best way to measure insulin sensitivity, standardization of insulin measurements, identification of strong surrogate biomarkers of IR, and the effective role of lifestyle intervention and medications in the prevention and treatment of IR.The aim of this review is to update each point of the consensus with the most recent available studies, with the goal of giving a picture of the current state of the scientific literature regarding IR in children, with a particular regard for issues that are not yet fully clarified.

Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits

BACKGROUND

A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans.

METHODS

We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses.

RESULTS

GWAS identified 39 significant (P value < 5 × 10-8) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals.

CONCLUSIONS

Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits.

Diabetes: discovery of insulin, genetic, epigenetic and viral infection mediated regulation

Diabetes mellitus, commonly referred to as diabetes, is a combination of many metabolic diseases. Insulin deficiency in our body is the main cause of diabetes. Insulin is one of the most well studied proteins, yet the genesis of its discovery was not getting much attention so far. Nevertheless, the history of the discovery of insulin is an exemplary of solving observational and scientific riddles, drudgery, patience and even professional turmoil. It is an inspiration for all medical personnel and scientists who are practising in the field of molecular medicine. Additionally, the genetic and epigenetic regulation of different types of diabetes needs to be addressed because of the widespread nature of the disease. Diabetes not only involves genetic predisposition but environmental factors, lifestyle etc. can be the major contributor for its inception. Nonetheless, viral infections at an early age are also found to trigger the onset of type I diabetes. In this review article, the history of the discovery of insulin is detailed along with the justification for the genetic and epigenetic regulatory mechanisms of diabetes and explained how viral infections can also trigger the onset of diabetes.

Identification of genetic variants for blood insulin level in sex-stratified Korean population and evaluation of the causal relationship between blood insulin level and polycystic ovary syndrome

BACKGROUND

Blood insulin level is an important risk factor for numerous disorders. Individual blood insulin level is known to be substantially influenced by genetic factors. Several genetic association studies identified a number of genetic variants for blood insulin level, but none of them was from a sex-stratified population.

OBJECTIVE

This study aimed to identify male- and female-specific genetic variants related to blood insulin level and to evaluate the causal relationship between blood insulin level and polycystic ovary syndrome (PCOS) that is likely caused by high insulin in Korean women.

METHODS

A genome-wide association study was conducted to identify genetic variants influencing blood insulin level in males (N = 4183) and females (N = 4659) in the Korean population. Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of the insulin variants identified from GWAS on PCOS in Korean women. Genetic association data for PCOS were obtained from a PCOS study cohort (946 cases, 976 controls) in Ewha Womans University Hospital.

RESULTS

GWAS linear regression analysis identified 13 female-specific SNPs and 13 male-specific SNPs showing suggestive associations (P < 10^-5) with blood insulin level. The results from two-sample MR analysis using the GWAS variants for PCOS indicated that genetically determined insulin level was not associated with the risk of PCOS in Korean women.

CONCLUSION

This study identified sex-specific genetic variants showing associations with insulin for the first time in East Asian populations. In addition, MR analysis using variants discovered from Korean women revealed that genetically determined high level of insulin is not the cause of PCOS.

Disparities in cardio metabolic risk between Black and White women with polycystic ovary syndrome: a systematic review and meta-analysis

OBJECTIVE

We conducted a systematic review and meta-analysis to summarize and quantitatively pool evidence on cardiometabolic health disparities between Black and White women with polycystic ovary syndrome in the United States in response to the call for further delineation of these disparities in the international evidence-based guideline for the assessment and management of polycystic ovary syndrome.

DATA SOURCES

Databases of MEDLINE, Web of Science, and Scopus were searched initially through March 05, 2020, and confirmed on September 11, 2020.

STUDY ELIGIBILITY CRITERIA

Observational studies documenting cardiometabolic risk profile (glucoregulatory, lipid profile, anthropometric, and blood pressure status) in Black and White women with polycystic ovary syndrome were included. Studies on children (<17 years old) and pregnant or menopausal-aged women (>50 years) were excluded. The primary outcome was fasting glucose. Furthermore, data on major cardiovascular events (stroke, coronary heart disease, heart failure) and mortality rate (cardiovascular death, total mortality) were evaluated.

METHODS

Data were pooled by random-effects models and expressed as mean differences and 95% confidence intervals. Studies were weighted based on the inverse of the variance. Heterogeneity was evaluated by Cochran Q and I2 statistics. Study methodologic quality was assessed by the Newcastle-Ottawa scale.

RESULTS

A total of 11 studies (N=2851 [652 Black and 2199 White]) evaluated cardiometabolic risk profile and all had high quality (Newcastle-Ottawa scale score of ≥8). No studies reported on cardiovascular events and mortality rate. Black women had comparable fasting glucose (-0.61 [-1.69 to 2.92] mg/dL; I2=62.5%), yet exhibited increased fasting insulin (6.76 [4.97-8.56] μIU/mL; I2=59.0%); homeostatic model assessment of insulin resistance (1.47 [0.86-2.08]; I2=83.2%); systolic blood pressure (3.32 [0.34-6.30] mm Hg; I2=52.0%); and decreased triglyceride (-32.56 [-54.69 to -10.42] mg/dL; I2=68.0%) compared with White women (all, P≤.03). Groups exhibited comparable total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and diastolic blood pressure (all, P≥.06).

CONCLUSIONS

Black women with polycystic ovary syndrome have a greater tendency for an adverse cardiometabolic risk profile (increased insulin, homeostatic model assessment of insulin resistance, and systolic blood pressure) despite lower triglycerides than White women. Our observations support the consideration of these disparities for diagnostic, monitoring, and management practices in Black women and for future guideline recommendations. Given the heterogeneity among studies, future research should address the relative contributions of biologic, environmental, socioeconomic, and healthcare factors to the observed disparities. Furthermore, longitudinal research is required to address patient-pressing complications, including cardiovascular events and mortality rate in Black women with polycystic ovary syndrome as a high-risk yet understudied population.

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.

Association of Baseline Characteristics With Insulin Sensitivity and β-Cell Function in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) Study Cohort

OBJECTIVE

We investigated sex and racial differences in insulin sensitivity, β-cell function, and glycated hemoglobin (HbA_1c) and the associations with selected phenotypic characteristics.

RESEARCH DESIGN AND METHODS

This is a cross-sectional analysis of baseline data from 3,108 GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) participants. All had type 2 diabetes diagnosed <10 years earlier and were on metformin monotherapy. Insulin sensitivity and β-cell function were evaluated using the HOMA of insulin sensitivity and estimates from oral glucose tolerance tests, including the Matsuda Index, insulinogenic index, C-peptide index, and oral disposition index (DI).

RESULTS

The cohort was 56.6 ± 10 years of age (mean ± SD), 63.8% male, with BMI 34.2 ± 6.7 kg/m², HbA_1c 7.5 ± 0.5%, and type 2 diabetes duration 4.0 ± 2.8 years. Women had higher DI than men but similar insulin sensitivity. DI was the highest in Black/African Americans, followed by American Indians/Alaska Natives, Asians, and Whites in descending order. Compared with Whites, American Indians/Alaska Natives had significantly higher HbA_1c, but Black/African Americans and Asians had lower HbA_1c. However, when adjusted for glucose levels, Black/African Americans had higher HbA_1c than Whites. Insulin sensitivity correlated inversely with BMI, waist-to-hip ratio, triglyceride-to-HDL-cholesterol ratio (TG/HDL-C), and the presence of metabolic syndrome, whereas DI was associated directly with age and inversely with BMI, HbA_1c, and TG/HDL-C.

CONCLUSIONS

In the GRADE cohort, β-cell function differed by sex and race and was associated with the concurrent level of HbA_1c. HbA_1c also differed among the races, but not by sex. Age, BMI, and TG/HDL-C were associated with multiple measures of β-cell function and insulin sensitivity.

Causal Pathways from Body Components and Regional Fat to Extensive Metabolic Phenotypes: A Mendelian Randomization Study

OBJECTIVE

The aim of this study was to explore the causal effects and pathways from body components to extensive metabolic phenotypes.

METHODS

Summarized data including 24 metabolic phenotypes from 10 consortiums were used to perform univariate, multivariable, and bidirectional Mendelian randomization analysis based on the network design.

RESULTS

For metabolically related biomarkers, a 1-SD increase in body fat mass (BFM) was robustly associated with increased fasting insulin, systolic blood pressure, diastolic blood pressure, and urate and decreased high-density lipoprotein cholesterol levels. For metabolically related diseases, the odds ratios and 95% CIs of a 1-SD increase in BFM were 1.76 (1.37 to 2.25) for type 2 diabetes mellitus (T2DM), 1.11 (1.09 to 1.13) for hypertension, 1.40 (1.25 to 1.57) for coronary artery disease, 1.41 (1.25 to 1.59) for myocardial infarction, 1.25 (1.12 to 1.40) for ischemic stroke, and 1.62 (1.02 to 2.57) for gout. The effects of body fat on diseases were mediated by extensive intermediate biomarkers, including blood pressure, lipids, glycemic traits, and urate. Regional fats had a similar effect with body fat in both absolute and relative scales, whereas fat-free components increased only the risk of T2DM 1.73 (1.11 to 2.68) and chronic kidney disease 1.51 (1.11 to 2.06).

CONCLUSIONS

Several potential pathways were found and confirmed the tremendous benefits of fat-lowering measures, including lowering of various regional fats. Future policies or interventions should focus more on the role of body fat.

Transcription Factor KLF14 and Metabolic Syndrome

Metabolic syndrome (MetSyn) is a combination of metabolic abnormalities that lead to the development of cardiovascular disease (CVD) and Type 2 Diabetes (T2D). Although various criteria for defining MetSyn exist, common abnormalities include abdominal obesity, elevated serum triglyceride, insulin resistance, and blood glucose, decreased high-density lipoprotein cholesterol (HDL-C), and hypertension. MetSyn prevalence has been increasing with the rise of obesity worldwide, with significantly higher prevalence in women compared with men and in Hispanics compared with Whites. Affected individuals are at a higher risk of developing T2D (5-fold) and CVD (2-fold). Heritability estimates for individual components of MetSyn vary between 40 and 70%, suggesting a strong contribution of an individual's genetic makeup to disease pathology. The advent of next-generation sequencing technologies has enabled large-scale genome-wide association studies (GWAS) into the genetics underlying MetSyn pathogenesis. Several such studies have implicated the transcription factor KLF14, a member of the Krüpple-like factor family (KLF), in the development of metabolic diseases, including obesity, insulin resistance, and T2D. How KLF14 regulates these metabolic traits and increases the risk of developing T2D, atherosclerosis, and liver dysfunction is still unknown. There have been some debate and controversial results with regards to its expression profile and functionality in various tissues, and a systematic review of current knowledge on KLF14 is lacking. Here, we summarize the research progress made in understanding the function of KLF14 and describe common attributes of its biochemical, physiological, and pathophysiological roles. We also discuss the current challenges in understanding the role of KLF14 in metabolism and provide suggestions for future directions.

Refining genome-wide associated loci for serum uric acid in individuals with African ancestry

OBJECTIVE

Serum uric acid is the end-product of purine metabolism and at high levels is a risk factor for several human diseases including gout and cardiovascular disease. Heritability estimates range from 0.32 to 0.63. Genome-wide association studies (GWAS) provide an unbiased approach to identify loci influencing serum uric acid. Here, we performed the first GWAS for serum uric acid in continental Africans, with replication in African Americans.

METHODS

Africans (n = 4126) and African Americans (n = 5007) were genotyped on high-density GWAS arrays. Efficient mixed model association, a variance component approach, was used to perform association testing for a total of ~ 18 million autosomal genotyped and imputed variants. CAVIARBF was used to fine map significant regions.

RESULTS

We identified two genome-wide significant loci: 4p16.1 (SLC2A9) and 11q13.1 (SLC22A12). At SLC2A9, the most strongly associated SNP was rs7683856 (P = 1.60 × 10-44). Conditional analysis revealed a second signal indexed by rs6838021 (P = 5.75 × 10-17). Gene expression and regulatory motif data prioritized a single-candidate causal variant for each signal. At SLC22A12, the most strongly associated SNP was rs147647315 (P = 6.65 × 10-25). Conditional analysis and functional annotation prioritized the missense variant rs147647315 (R (Arg) > H (His)) as the sole causal variant. Functional annotation of these three signals implicated processes in skeletal muscle, subcutaneous adipose tissue and the kidneys, respectively.

CONCLUSIONS

This first GWAS of serum uric acid in continental Africans identified three associations at two loci, SLC2A9 and SLC22A12. The combination of weak linkage disequilibrium in Africans and functional annotation led to the identification of candidate causal SNPs for all three signals. Each candidate causal variant implicated a different cell type. Collectively, the three associations accounted for 4.3% of the variance of serum uric acid.

Class Balanced Multifactor Dimensionality Reduction to Detect Gene-Gene Interactions

Detecting gene-gene interactions in single-nucleotide polymorphism data is vital for understanding disease susceptibility. However, existing approaches may be limited by the sample size in case-control studies. Herein, we propose a balance approach for the multifactor dimensionality reduction (BMDR) method to increase the accuracy of estimates of the prediction error rate in small samples. BMDR explicitly selects the best model by evaluating the average of prediction error rates over k-fold cross-validation without cross-validation consistency selection. In this study, we used several epistatic models with and without marginal effects under different parameter settings (heritability and minor allele frequencies) to evaluate the performance of existing approaches. Using simulated data sets, BMDR successfully detected gene-gene interactions, particularly for data sets with small sample sizes. A large data set was obtained from the Wellcome Trust Case Control Consortium, and results indicated that BMDR could effectively detect significant gene-gene interactions.

Genome-wide association analysis suggests novel loci underlying thyroid antibodies in Hashimoto's thyroiditis

Thyroid antibodies against thyroglobulin (TgAb) and thyroid peroxidase (TPOAb) are key markers of Hashimoto's thyroiditis (HT), the most common autoimmune thyroid disorder. Genetic determinants of thyroid antibodies are still poorly known, especially as they were not studied in patients with thyroid diseases. We performed the first genome-wide association analysis of thyroid antibodies in 430 HT patients that may be considered as population extremes for thyroid antibodies distribution. We detected two suggestively associated genetic variants with TgAb, rs6972286 close to ANKRD7 and LSM8 (P = 2.34 × 10^-7) and rs756763 inside CA10 (P = 6.05 × 10^-7), and one with TPOAb, rs12507813 positioned between TRIM61 and TRIM60 (P = 4.95 × 10^-7). Bivariate analysis resulted with three suggestively associated genetic variants that predispose to both antibodies: rs13190616 inside RP11-138J23.1 (P = 2.01 × 10^-6), rs561030786 close to DUBR (P = 7.33 × 10^-6) and rs12713034 inside FSHR (P = 7.66 × 10^-6). All identified genomic regions have a substantial literature record of involvement with female-related traits, immune-mediated diseases and personality traits that are all characterized by increased thyroid antibody levels. Our findings demonstrate the existence of genetic overlap between thyroid autoimmunity in HT and different non-thyroid diseases characterized by the presence of thyroid antibodies. We also suggest that genetic variants that regulate antibody levels may differ between HT patients and individuals with normal thyroid function.

Identification of Differentially Expressed Genes and Pathways for Abdominal Fat Deposition in Ovariectomized and Sham-Operated Chickens

Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have also been reported. In this study, the gene expression profiles of AF tissue in ovariectomized and sham-operated chickens were determined to identify differentially expressed genes (DEGs) and pathways to explore the molecular mechanisms underlying AF accumulation. Comparing the ovariectomized group and the sham-operated group, the abdominal fat weight (AFW) and abdominal fat percentage (AFP) were increased significantly (p < 0.05) at 14 and 19 weeks after ovariectomy. According to the gene expression profiling analysis, 108 DEGs of fat metabolism were screened from 1461 DEGs. Among them, ABCA1, ABCACA, LPL, CREB1, PNPLA2, which are involved in glycerolipid—or steroid—associated biological processes, and the hormone receptor genes, ESR1 and PRLR, were down-regulated significantly in the ovariectomized group compared to the sham-operated group (p < 0.05). Conversely, CETP, DGAT2, DHCR24, HSD17B7 and MSMO1, were significantly up-regulated (p < 0.05) after ovariectomy. Based on the DEGs, the glycerolipid metabolism, steroid biosynthesis, and other signaling pathways (MAPK, TGF-β, and adhesion pathways, etc.) were enriched, which may also contribute to the regulation of AF deposition. Our data suggest that AF deposition was significantly increased in ovariectomized chickens by the down-regulation of the decomposition genes of glycerolipid metabolism, which inhibits AF degradation, and the up-regulation of steroid biosynthesis genes, which increases fat accumulation. These findings provide new insights into the molecular mechanisms of fat deposition in the ovariectomized chickens.

Insulin Resistance and Metabolic Syndrome: Clinical and Laboratory Associations in African Americans Without Diabetes in the Hemochromatosis and Iron Overload Screening Study

BACKGROUND

We sought to determine associations with insulin resistance (IR) and metabolic syndrome (MetS) in African Americans.

METHODS

We studied African American adults without diabetes in a postscreening examination. Participants included Cases: transferrin saturation (TS) >50% and serum ferritin (SF) >300 μg/L (M), and TS >45% and SF >200 μg/L (F), regardless of HFE genotype; and Controls: TS/SF 25th to 75th percentiles and HFE wt/wt (wild type). We excluded participants with fasting <8 h; fasting glucose >126 mg/dL; hepatitis B or C; cirrhosis; pregnancy; or incomplete datasets. We analyzed age; sex; Case/Control; body mass index (BMI); systolic and diastolic blood pressures; neutrophils; lymphocytes; alanine aminotransferase; aspartate aminotransferase; elevated C-reactive protein (CRP >0.5 mg/L); TS; and SF. We computed homeostasis model assessment of insulin resistance (HOMA-IR) using fasting serum glucose and insulin, and defined IR as HOMA-IR fourth quartile (≥2.42).

RESULTS

There were 312 Cases and 86 Controls (56.3% men). Ninety-one percent had HFE wt/wt. None had HFE p.C282Y. A significant increasing trend across HOMA-IR quartiles was observed for BMI only. Multivariable regression on HOMA-IR revealed significant positive associations: age; BMI; lymphocytes; SF; and CRP >0.5 mg/L; and significant negative associations: neutrophils and TS. Logistic regression on IR revealed BMI [odds ratio (OR) 1.3 (95% confidence interval 1.2-1.4)] and CRP >0.5 mg/L [OR 2.7 (1.2-6.3)]. Fourteen participants (3.5%) had MetS. Logistic regression on MetS revealed one association: IR [OR 7.4 (2.1-25.2)].

CONCLUSIONS

In African Americans without diabetes, IR was associated with BMI and CRP >0.5 mg/L, after adjustment for other variables. MetS was associated with IR alone.

Changes of glucose levels precede dementia in African-Americans with diabetes but not in Caucasians

INTRODUCTION

Changes in glucose levels may represent a powerful metabolic indicator of dementia in African-Americans with diabetes. It is unclear whether these changes also occur in Caucasians.

METHODS

A secondary data analysis using electronic medical records from 5228 African-Americans and Caucasians aged ≥65 years was carried out. Mixed effects models with repeated serum glucose measurements were used to compare changes in glucose levels between African-Americans and Caucasian patients with and without incident dementia.

RESULTS

African-Americans and Caucasians with diabetes had significantly different changes in glucose levels by dementia status (P < .0001). African-Americans experienced a significant decline in glucose levels before the dementia diagnosis (estimated glucose decline 1.3421 mg/dL per year, P < .0001) than those who did not develop dementia. Caucasians with and without dementia showed stable glucose levels over time (P = .3071).

DISCUSSION

Significant changes in glucose levels precede dementia in African-American patients with diabetes but not in Caucasians.

No novel, high penetrant gene might remain to be found in Japanese patients with unknown MODY

MODY 5 and 6 have been shown to be low-penetrant MODYs. As the genetic background of unknown MODY is assumed to be similar, a new analytical strategy is applied here to elucidate genetic predispositions to unknown MODY. We examined to find whether there are major MODY gene loci remaining to be identified using SNP linkage analysis in Japanese. Whole-exome sequencing was performed with seven families with typical MODY. Candidates for novel MODY genes were examined combined with in silico network analysis. Some peaks were found only in either parametric or non-parametric analysis; however, none of these peaks showed a LOD score greater than 3.7, which is approved to be the significance threshold of evidence for linkage. Exome sequencing revealed that three mutated genes were common among 3 families and 42 mutated genes were common in two families. Only one of these genes, MYO5A, having rare amino acid mutations p.R849Q and p.V1601G, was involved in the biological network of known MODY genes through the intermediary of the INS. Although only one promising candidate gene, MYO5A, was identified, no novel, high penetrant MODY genes might remain to be found in Japanese MODY.

Maternal and fetal genetic contribution to gestational weight gain

BACKGROUND

Clinical recommendations to limit gestational weight gain (GWG) imply high GWG is causally related to adverse outcomes in mother or offspring, but GWG is the sum of several inter-related complex phenotypes (maternal fat deposition and vascular expansion, placenta, amniotic fluid and fetal growth). Understanding the genetic contribution to GWG could help clarify the potential effect of its different components on maternal and offspring health. Here we explore the genetic contribution to total, early and late GWG.

PARTICIPANTS AND METHODS

A genome-wide association study was used to identify maternal and fetal variants contributing to GWG in up to 10 543 mothers and 16 317 offspring of European origin, with replication in 10 660 mothers and 7561 offspring. Additional analyses determined the proportion of variability in GWG from maternal and fetal common genetic variants and the overlap of established genome-wide significant variants for phenotypes relevant to GWG (for example, maternal body mass index (BMI) and glucose, birth weight).

RESULTS

Approximately 20% of the variability in GWG was tagged by common maternal genetic variants, and the fetal genome made a surprisingly minor contribution to explain variation in GWG. Variants near the pregnancy-specific beta-1 glycoprotein 5 (PSG5) gene reached genome-wide significance (P=1.71 × 10-8) for total GWG in the offspring genome, but did not replicate. Some established variants associated with increased BMI, fasting glucose and type 2 diabetes were associated with lower early, and higher later GWG. Maternal variants related to higher systolic blood pressure were related to lower late GWG. Established maternal and fetal birth weight variants were largely unrelated to GWG.

CONCLUSIONS

We found a modest contribution of maternal common variants to GWG and some overlap of maternal BMI, glucose and type 2 diabetes variants with GWG. These findings suggest that associations between GWG and later offspring/maternal outcomes may be due to the relationship of maternal BMI and diabetes with GWG.

Weighted likelihood inference of genomic autozygosity patterns in dense genotype data

Background

Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns.

Methods

We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data.

Results

Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies.

Conclusions

This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4312-3) contains supplementary material, which is available to authorized users.

Genetic determinants of circulating GIP and GLP-1 concentrations

The secretion of insulin and glucagon from the pancreas and the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) from the gastrointestinal tract is essential for glucose homeostasis. Several novel treatment strategies for type 2 diabetes (T2D) mimic GLP-1 actions or inhibit incretin degradation (DPP4 inhibitors), but none is thus far aimed at increasing the secretion of endogenous incretins. In order to identify new potential therapeutic targets for treatment of T2D, we performed a meta-analysis of a GWAS and an exome-wide association study of circulating insulin, glucagon, GIP, and GLP-1 concentrations measured during an oral glucose tolerance test in up to 7,828 individuals. We identified 6 genome-wide significant functional loci associated with plasma incretin concentrations in or near the SLC5A1 (encoding SGLT1), GIPR, ABO, GLP2R, F13A1, and HOXD1 genes and studied the effect of these variants on mRNA expression in pancreatic islet and on metabolic phenotypes. Immunohistochemistry showed expression of GIPR, ABO, and HOXD1 in human enteroendocrine cells and expression of ABO in pancreatic islets, supporting a role in hormone secretion. This study thus provides candidate genes and insight into mechanisms by which secretion and breakdown of GIP and GLP-1 are regulated.

Genetics of Insulin Resistance and the Metabolic Syndrome

Insulin resistance and the metabolic syndrome are complex metabolic traits and key risk factors for the development of cardiovascular disease. They result from the interplay of environmental and genetic factors but the full extent of the genetic background to these conditions remains incomplete. Large-scale genome-wide association studies have helped advance the identification of common genetic variation associated with insulin resistance and the metabolic syndrome, and more recently, exome sequencing has allowed the identification of rare variants associated with the pathogenesis of these conditions. Many variants associated with insulin resistance are directly involved in glucose metabolism; however, functional studies are required to assess the contribution of other variants to the development of insulin resistance. Many genetic variants involved in the pathogenesis of the metabolic syndrome are associated with lipid metabolism.

Genetic sharing with coronary artery disease identifies potential novel loci for bone mineral density

Bone mineral density (BMD) is a complex trait with high missing heritability. Numerous evidences have shown that BMD variation has a relationship with coronary artery disease (CAD). This relationship may come from a common genetic basis called pleiotropy. By leveraging the pleiotropy with CAD, we may be able to improve the detection power of genetic variants associated with BMD. Using a recently developed conditional false discovery rate (cFDR) method, we jointly analyzed summary statistics from two large independent genome wide association studies (GWAS) of lumbar spine (LS) BMD and CAD. Strong pleiotropic enrichment and 7 pleiotropic SNPs were found for the two traits. We identified 41 SNPs for LS BMD (cFDR<0.05), of which 20 were replications of previous GWASs and 21 were potential novel SNPs that were not reported before. Four genes encompassed by 9 cFDR-significant SNPs were partially validated in the gene expression assay. Further functional enrichment analysis showed that genes corresponding to the cFDR-significant LS BMD SNPs were enriched in GO terms and KEGG pathways that played crucial roles in bone metabolism (adjP<0.05). In protein-protein interaction analysis, strong interactions were found between the proteins produced by the corresponding genes. Our study demonstrated the reliability and high-efficiency of the cFDR method on the detection of trait-associated genetic variants, the present findings shed novel insights into the genetic variability of BMD as well as the shared genetic basis underlying osteoporosis and CAD.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

The genomic landscape of African populations in health and disease

A deeper appreciation of the complex architecture of African genomes is critical to the global effort to understand human history, biology and differential distribution of disease by geography and ancestry. Here, we report on how the growing engagement of African populations in genome science is providing new insights into the forces that shaped human genomes before and after the Out-of-Africa migrations. As a result of this human evolutionary history, African ancestry populations have the greatest genomic diversity in the world, and this diversity has important ramifications for genomic research. In the case of pharmacogenomics, for instance, variants of consequence are not limited to those identified in other populations, and diversity within African ancestry populations precludes summarizing risk across different African ethnic groups. Exposure of Africans to fatal pathogens, such as Plasmodium falciparum, Lassa Virus and Trypanosoma brucei rhodesiense, has resulted in elevated frequencies of alleles conferring survival advantages for infectious diseases, but that are maladaptive in modern-day environments. Illustrating with cardiometabolic traits, we show that while genomic research in African ancestry populations is still in early stages, there are already many examples of novel and African ancestry-specific disease loci that have been discovered. Furthermore, the shorter haplotypes in African genomes have facilitated fine-mapping of loci discovered in other human ancestry populations. Given the insights already gained from the interrogation of African genomes, it is imperative to continue and increase our efforts to describe genomic risk in and across African ancestry populations.

Genome-wide association studies of albuminuria: towards genetic stratification in diabetes?

Genome-wide association studies (GWAS) have been very successful in unraveling the polygenic structure of several complex diseases and traits. In the case of albuminuria, despite the large sample size achieved by some studies, results look sparse with a limited number of loci reported so far. This review searched for GWAS studies of albumin excretion, albuminuria, and proteinuria. The resulting picture sets elements of uniqueness for albuminuria GWAS with respect to other complex traits. So far, very few loci associated with albuminuria have been validated by means of genome-wide significant evidence or formal replication. With rare exceptions, the validated loci are ethnicity specific. Within a given ethnicity, variants are common and have relatively large effects, especially in the presence of diabetes. In most cases, the identified variants were functional and a biological involvement of the target genes in renal damage was established. Recently reported variants associated with albuminuria in diabetes may be potentially combined into a genetic risk score, making it possible to rank diabetic patients by increasing risk of albuminuria. Validation of this model is required. To expand the understanding of the biological basis of albumin excretion regulation, future initiatives should achieve larger sample sizes and favor a transethnic study design.

Using the Neandertal genome to study the evolution of small insertions and deletions in modern humans

Background

Small insertions and deletions occur in humans at a lower rate compared to nucleotide changes, but evolve under more constraint than nucleotide changes. While the evolution of insertions and deletions have been investigated using ape outgroups, the now available genome of a Neandertal can shed light on the evolution of indels in more recent times.

Results

We used the Neandertal genome together with several primate outgroup genomes to differentiate between human insertion/deletion changes that likely occurred before the split from Neandertals and those that likely arose later. Changes that pre-date the split from Neandertals show a smaller proportion of deletions than those that occurred later. The presence of a Neandertal-shared allele in Europeans or Asians but the absence in Africans was used to detect putatively introgressed indels in Europeans and Asians. A larger proportion of these variants reside in intergenic regions compared to other modern human variants, and some variants are linked to SNPs that have been associated with traits in modern humans.

Conclusions

Our results are in agreement with earlier results that suggested that deletions evolve under more constraint than insertions. When considering Neandertal introgressed variants, we find some evidence that negative selection affected these variants more than other variants segregating in modern humans. Among introgressed variants we also identify indels that may influence the phenotype of their carriers. In particular an introgressed deletion associated with a decrease in the time to menarche may constitute an example of a former Neandertal-specific trait contributing to modern human phenotypic diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-1018-8) contains supplementary material, which is available to authorized users.

Thyroid Signaling, Insulin Resistance, and 2 Diabetes Mellitus: A Mendelian Randomization Study

Context

Increasing evidence suggests an association between thyroid-stimulating hormone (TSH), free thyroxine (fT4), and deiodinases with insulin resistance and type 2 diabetes mellitus (T2D).

Objective

We examined whether TSH and fT4 levels and deiodinases are causally associated with insulin resistance and T2D, using Mendelian randomization.

Methods

We selected 20 genetic variants for TSH level and four for fT4 level (identified in a genome-wide association study (GWAS) meta-analysis of European-ancestry cohorts) as instrumental variables for TSH and fT4 levels, respectively. We used summary data from GWASs on the outcomes T2D [Diabetes, Genetics Replication and Meta-analysis (DIAGRAM), n = 12,171 cases and n = 56,862 control subjects] and glycemic traits in patients without diabetes [Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), n = 46,186 for fasting glucose and insulin and n = 46,368 for hemoglobin A1c]. To examine whether the associations between TSH/fT4 levels and the study outcomes were causal, we combined the effects of the genetic instruments. Furthermore, we examined the associations among 16 variants in DIO1, DIO2, DIO3, and T2D and glycemic traits.

Results

We found no evidence for an association between the combined genetic instrumental variables for TSH and fT4 and the study outcomes. For example, we did not observe a genetically determined association between high TSH level and T2D (odds ratio, 0.91 per standard deviation TSH increase; 95% confidence interval, 0.78 to 1.07). Selected genetic variants in DIO1 (e.g., rs7527713) were associated with measures of insulin resistance.

Conclusion

We found no evidence for a causal association between circulatory levels of TSH and fT4 with insulin resistance and T2D, but we found suggestive evidence that DIO1 affects glucose metabolism.

Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations

Genome-wide association studies (GWAS) have successfully identified genetic loci associated with glycemic traits. However, characterizing the functional significance of these loci has proven challenging. We sought to gain insights into the regulation of fasting insulin and fasting glucose through the use of gene expression microarray data from peripheral blood samples of participants without diabetes in the Framingham Heart Study (FHS) (n = 5,056), the Rotterdam Study (RS) (n = 723), and the InCHIANTI Study (Invecchiare in Chianti) (n = 595). Using a false discovery rate q <0.05, we identified three transcripts associated with fasting glucose and 433 transcripts associated with fasting insulin levels after adjusting for age, sex, technical covariates, and complete blood cell counts. Among the findings, circulating IGF2BP2 transcript levels were positively associated with fasting insulin in both the FHS and RS. Using 1000 Genomes-imputed genotype data, we identified 47,587 cis-expression quantitative trait loci (eQTL) and 6,695 trans-eQTL associated with the 433 significant insulin-associated transcripts. Of note, we identified a trans-eQTL (rs592423), where the A allele was associated with higher IGF2BP2 levels and with fasting insulin in an independent genetic meta-analysis comprised of 50,823 individuals. We conclude that integration of genomic and transcriptomic data implicate circulating IGF2BP2 mRNA levels associated with glucose and insulin homeostasis.

Phenomics of Vascular Disease: The Systematic Approach to the Combination Therapy

Vascular diseases are usually caused by multifactorial pathogeneses involving genetic and environmental factors. Our current understanding of vascular disease is, however, based on the focused genotype/phenotype studies driven by the “one-gene/one-phenotype” hypothesis. Drugs with “pure target” at individual molecules involved in the pathophysiological pathways are the mainstream of current clinical treatments and the basis of combination therapy of vascular diseases. Recently, the combination of genomics, proteomics, and metabolomics has unraveled the etiology and pathophysiology of vascular disease in a big-data fashion and also revealed unmatched relationships between the omic variability and the much narrower definition of various clinical phenotypes of vascular disease in individual patients. Here, we introduce the phenomics strategy that will change the conventional focused phenotype/genotype/genome study to a new systematic phenome/genome/proteome approach to the understanding of pathophysiology and combination therapy of vascular disease. A phenome is the sum total of an organism’s phenotypic traits that signify the expression of genome and specific environmental influence. Phenomics is the study of phenome to quantitatively correlate complex traits to variability not only in genome, but also in transcriptome, proteome, metabolome, interactome, and environmental factors by exploring the systems biology that links the genomic and phenomic spaces. The application of phenomics and the phenome-wide associated study (PheWAS) will not only identify a systemically-integrated set of biomarkers for diagnosis and prognosis of vascular disease but also provide novel treatment targets for combination therapy and thus make a revolutionary paradigm shift in the clinical treatment of these devastating diseases.

On the problem of type 2 diabetes-related mortality in the Canary Islands, Spain. The DARIOS Study

AIMS

To compare diabetes-related mortality rates and factors associated with this disease in the Canary Islands compared with other 10 Spanish regions.

METHODS

In a cross-sectional study of 28,887 participants aged 35-74 years in Spain, data were obtained for diabetes, hypertension, dyslipidemia, obesity, insulin resistance (IR), and metabolic syndrome. Healthcare was measured as awareness, treatment and control of diabetes, dyslipidemia, and hypertension. Standardized mortality rate ratios (SRR) were calculated for the years 1981 to 2011 in the same regions.

RESULTS

Diabetes, obesity, and hypertension were more prevalent in people under the age of 64 in the Canary Islands than in Spain. For all ages, metabolic syndrome and insulin resistance (IR) were also more prevalent in those from the Canary Islands. Healthcare parameters were similar in those from the Canary Islands and the rest of Spain. Diabetes-related mortality in the Canary Islands was the highest in Spain since 1981; the maximum SRR was reached in 2011 in men (6.3 versus the region of Madrid; p<0.001) and women (9.5 versus Madrid; p<0.001). Excess mortality was prevalent from the age of 45 years and above.

CONCLUSIONS

Diabetes-related mortality is higher in the Canary Islands population than in any other Spanish region. The high mortality and prevalence of IR warrants investigation of the genetic background associated with a higher incidence and poor prognosis for diabetes in this population. The rise in SRR calls for a rapid public health policy response.

Association of ADIPOQ gene with type 2 diabetes and related phenotypes in African American men and women: the Jackson Heart Study

BACKGROUND

African Americans experience disproportionately higher prevalence of type 2 diabetes and related risk factors. Little research has been done on the association of ADIPOQ gene on type 2 diabetes, plasma adiponectin, blood glucose, HOMA-IR and body mass index (BMI) in African Americans. The objective of our research was to assess such associations with selected SNPs. The study included a sample of 3,020 men and women from the Jackson Heart Study who had ADIPOQ genotyping information. Unadjusted and adjusted regression models with covariates were used with type 2 diabetes and related phenotypes as the outcome stratified by sex.

RESULTS

There was no association between selected ADIPOQ SNPs with type 2 diabetes, blood glucose, or BMI in men or women. There was a significant association between variant rs16861205 and lower adiponectin in women with minor allele A in the fully adjusted model (β(SE) p = -.13(0.05), 0.003). There was also a significant association with variant rs7627128 and lower HOMA-IR among men with minor allele A in the fully adjusted model (β(SE) p = -0.74(0.20), 0.0002).

CONCLUSIONS

These findings represent new insights regarding the association of ADIPOQ gene and type 2 diabetes and related phenotypes in African American men and women.

Thermal proteome profiling monitors ligand interactions with cellular membrane proteins

We extended thermal proteome profiling to detect transmembrane protein-small molecule interactions in cultured human cells. When we assessed the effects of detergents on ATP-binding profiles, we observed shifts in denaturation temperature for ATP-binding transmembrane proteins. We also observed cellular thermal shifts in pervanadate-induced T cell-receptor signaling, delineating the membrane target CD45 and components of the downstream pathway, and with drugs affecting the transmembrane transporters ATP1A1 and MDR1.

Genetics of Type 2 Diabetes in African Americans

Type 2 diabetes (T2D) is a global health problem showing substantial ethnic disparity in disease prevalence. African Americans have one of the highest prevalence of T2D in the USA but little is known about their genetic risks. This review summarizes the findings of genetic regions and loci associated with T2D and related glycemic traits using linkage, admixture, and association approaches in populations of African ancestry. In particular, findings from genome-wide association and exome chip studies suggest the presence of both ancestry-specific and shared loci for T2D and glycemic traits. Among the European-identified loci that are transferable to individuals of African ancestry, allelic heterogeneity as well as differential linkage disequilibrium and risk allele frequencies pose challenges and opportunities for fine mapping and identification of causal variant(s) by trans-ancestry meta-analysis. More genetic research is needed in African ancestry populations including the next-generation sequencing to improve the understanding of genetic architecture of T2D.

Perhexiline activates KLF14 and reduces atherosclerosis by modulating ApoA-I production

Recent genome-wide association studies have revealed that variations near the gene locus encoding the transcription factor Krüppel-like factor 14 (KLF14) are strongly associated with HDL cholesterol (HDL-C) levels, metabolic syndrome, and coronary heart disease. However, the precise mechanisms by which KLF14 regulates lipid metabolism and affects atherosclerosis remain largely unexplored. Here, we report that KLF14 is dysregulated in the liver of 2 dyslipidemia mouse models. We evaluated the effects of both KLF14 overexpression and genetic inactivation and determined that KLF14 regulates plasma HDL-C levels and cholesterol efflux capacity by modulating hepatic ApoA-I production. Hepatic-specific Klf14 deletion in mice resulted in decreased circulating HDL-C levels. In an attempt to pharmacologically target KLF14 as an experimental therapeutic approach, we identified perhexiline, an approved therapeutic small molecule presently in clinical use to treat angina and heart failure, as a KLF14 activator. Indeed, in WT mice, treatment with perhexiline increased HDL-C levels and cholesterol efflux capacity via KLF14-mediated upregulation of ApoA-I expression. Moreover, perhexiline administration reduced atherosclerotic lesion development in apolipoprotein E-deficient mice. Together, these results provide comprehensive insight into the KLF14-dependent regulation of HDL-C and subsequent atherosclerosis and indicate that interventions that target the KLF14 pathway should be further explored for the treatment of atherosclerosis.

Recent advances in understanding the genetic architecture of type 2 diabetes

Genome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c). At the end of 2011, established loci (P < 5 × 10(-8)) totaled 55 for T2D and 32 for glycemic traits. Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05] variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations. Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci. Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered. Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes.

Racial Disparities in the Pathogenesis of Type 2 Diabetes and its Subtypes in the African Diaspora: A New Paradigm

The global epidemic of diabetes has extended to the developing countries including Sub-Sahara Africa. In this context, blacks with type 2 diabetes in the African Diaspora continue to manifest 1.5-2 times higher prevalent rates than in their white counterparts. Previous studies have demonstrated that blacks with and without type 2 diabetes have alterations in hepatic and peripheral insulin sensitivity, beta-cell function, and hepatic insulin clearance as well as hepatic glucose dysregulation when compared to whites. In addition, non-diabetic blacks in the African Diaspora manifest multiple metabolic mediators that predict type 2 diabetes and its subtypes. These pathogenic modifiers include differences in subclinical inflammation, oxidative stress burden, and adipocytokines in blacks in the African Diaspora prior to clinical diagnosis. Consequently, blacks in the African Diaspora manifest subtypes of type 2 diabetes, including ketosis-prone diabetes and J type diabetes. Given the diversity of type 2 diabetes in blacks in the African Diaspora, we hypothesize that blacks manifest multiple early pathogenic defects prior to the diagnosis of type 2 diabetes and its subtypes. These metabolic alterations have strong genetic component, which appears to play pivotal and primary role in the pathogenesis of type 2 diabetes and its subtypes in blacks in the African Diaspora. However, environmental factors must also be considered as major contributors to the higher prevalence of type 2 diabetes and its subtypes in blacks in the African Diaspora. These multiple alterations should be targets for early prevention of type 2 diabetes in blacks in the African Diaspora.

Genetics of type 2 diabetes-pitfalls and possibilities

Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

Association of African genetic ancestry with fasting glucose and HbA1c levels in non-diabetic individuals: the Boston Area Community Health (BACH) Prediabetes Study

AIMS/HYPOTHESIS

To test among diabetes-free urban community-dwelling adults the hypothesis that the proportion of African genetic ancestry is positively associated with glycaemia, after accounting for other continental ancestry proportions, BMI and socioeconomic status (SES).

METHODS

The Boston Area Community Health cohort is a multi-stage 1:1:1 stratified random sample of self-identified African-American, Hispanic and white adults from three Boston inner city areas. We measured 62 ancestry informative markers, fasting glucose (FG), HbA1c, BMI and SES (income, education, occupation and insurance status) and analysed 1,387 eligible individuals (379 African-American, 411 Hispanic, 597 white) without clinical or biochemical evidence of diabetes. We used three-heritage multinomial linear regression models to test the association of FG or HbA1c with genetic ancestry proportion adjusted for: (1) age and sex; (2) age, sex and BMI; and (3) age, sex, BMI and SES.

RESULTS

Mean age- and sex-adjusted FG levels were 5.73 and 5.54 mmol/l among those with 100% African or European ancestry, respectively. Using per cent European ancestry as the referent, each 1% increase in African ancestry proportion was associated with an age- and sex-adjusted FG increase of 0.0019 mmol/l (p = 0.01). In the BMI- and SES-adjusted model the slope was 0.0019 (p = 0.02). Analysis of HbA1c gave similar results.

CONCLUSIONS/INTERPRETATION

A greater proportion of African genetic ancestry is independently associated with higher FG levels in a non-diabetic community-based cohort, even accounting for other ancestry proportions, obesity and SES. The results suggest that differences between African-Americans and whites in type 2 diabetes risk may include genetically mediated differences in glucose homeostasis.

Insights into the genetic basis of type 2 diabetes

Type 2 diabetes is one of the most common complex diseases, of which considerable efforts have been made to unravel the pathophysiological mechanisms. Recently, large‐scale genome‐wide association (GWA) studies have successfully identified genetic loci robustly associated with type 2 diabetes by searching susceptibility variants across the entire genome in an unbiased, hypothesis‐free manner. The number of loci has climbed from just three in 2006 to approximately 70 today. For the common type 2 diabetes‐associated variants, three features have been noted. First, genetic impacts of individual variants are generally modest; mostly, allelic odds ratios range between 1.06 and 1.20. Second, most of the loci identified to date are not in or near obvious candidate genes, but some are often located in the intergenic regions. Third, although the number of loci is limited, there might be some population specificity in type 2 diabetes association. Although we can estimate a single or a few target genes for individual loci detected in GWA studies by referring to the data for experiments in vitro, biological function remains largely unknown for a substantial part of such target genes. Nevertheless, new biology is arising from GWA study discoveries; for example, genes implicated in β‐cell dysfunction are over‐represented within type 2 diabetes‐associated regions. Toward translational advances, we have just begun to face new challenges – elucidation of multifaceted (i.e., molecular, cellular and physiological) mechanistic insights into disease biology by considering interaction with the environment. The present review summarizes recent advances in the genetics of type 2 diabetes, together with its realistic potential.

Shared and independent colorectal cancer risk alleles in TGFβ-related genes in African and European Americans

Genome-wide association studies (GWAS) in colorectal cancer (CRC) identified five regions near transforming growth factor β-related genes BMP4, GREM1, CDH1, SMAD7 and RPHN2. The true risk alleles remain to be identified in these regions, and their role in CRC risk in non-European populations has been understudied. Our previous work noted significant genetic heterogeneity between African Americans (AAs) and European Americans (EAs) for single nucleotide polymorphisms (SNPs) identified in GWAS. We hypothesized that associations may not have been replicated in AAs due to differential or independent genetic structures. In order to test this hypothesis, we genotyped 195 tagging SNPs across these five gene regions in 1194 CRC cases (795 AAs and 399 EAs) and 1352 controls (985 AAs and 367 EAs). Imputation was performed, and association testing of genotyped and imputed SNPs included ancestry, age and sex as covariates. In two of the five genes originally associated with CRC, we found evidence for association in AAs including rs1862748 in CDH1 (OR(Add) = 0.82, P = 0.02) and in GREM1 the SNPs rs10318 (OR(Rec) = 60.1, P = 0.01), rs11632715 (OR(Rec) = 2.36; P = 0.004) and rs12902616 (OR(Rec) = 1.28, P = 0.005), the latter which is in linkage disequilibrium with the previously identified SNP rs4779584. Testing more broadly for associations in these gene regions in AAs, we noted three statistically significant association peaks in GREM1 and RHPN2 that were not identified in EAs. We conclude that some CRC risk alleles are shared between EAs and AAs and others are population specific.

Genetic and functional evidence for a locus controlling otitis media at chromosome 10q26.3

BACKGROUND

Otitis media (OM) is a common childhood disease characterised by middle ear effusion and inflammation. Susceptibility to recurrent acute OM and chronic OM with effusion is 40-70% heritable. Linkage studies provide evidence for multiple putative OM susceptibility loci. This study attempts to replicate these linkages in a Western Australian (WA) population, and to identify the etiological gene(s) in a replicated region.

METHODS

Microsatellites were genotyped in 468 individuals from 101 multicase families (208 OM cases) from the WA Family Study of OM (WAFSOM) and non-parametric linkage analysis carried out in ALLEGRO. Association mapping utilized dense single nucleotide polymorphism (SNP) data extracted from Illumina 660 W-Quad analysis of 256 OM cases and 575 controls from the WA Pregnancy Cohort (Raine) Study. Logistic regression analysis was undertaken in ProbABEL. RT-PCR was used to compare gene expression in paired adenoid and tonsil samples, and in epithelial and macrophage cell lines. Comparative genomics methods were used to identify putative regulatory elements and transcription factor binding sites potentially affected by associated SNPs.

RESULTS

Evidence for linkage was observed at 10q26.3 (Zlr = 2.69; P = 0.0036; D10S1770) with borderline evidence for linkage at 10q22.3 (Zlr = 1.64; P = 0.05; D10S206). No evidence for linkage was seen at 3p25.3, 17q12, or 19q13.43. Peak association at 10q26.3 was in the intergenic region between TCERG1L and PPP2R2D (rs7922424; P = 9.47 × 10-6), immediately under the peak of linkage. Independent associations were observed at DOCK1 (rs9418832; P = 7.48 × 10-5) and ADAM12 (rs7902734; P = 8.04 × 10-4). RT-PCR analysis confirmed expression of all 4 genes in adenoid samples. ADAM12, DOCK1 and PPP2R2D, but not TCERG1L, were expressed in respiratory epithelial and macrophage cell lines. A significantly associated polymorphism (rs7087384) in strong LD with the top SNP (rs7922424; r2 = 0.97) alters a transcription factor binding site (CREB/CREBP) in the intergenic region between TCERG1L and PPP2R2D.

CONCLUSIONS

OM linkage was replicated at 10q26.3. Whilst multiple genes could contribute to this linkage, the weight of evidence supports PPP2R2D, a TGF-β/Activin/Nodal pathway modulator, as the more likely functional candidate lying immediately under the linkage peak for OM susceptibility at chromosome 10q26.3.

Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits

Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects. Important mechanistic insights have been gained regarding the physiological role of T2D loci in disease predisposition through the elucidation of their contribution to glycaemic trait variability. Further investigation is warranted to define causal variants within these loci, including functional characterisation of associated variants, to dissect their role in disease mechanisms and to enable clinical translation.

The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial

OBJECTIVE

To investigate the association of risk alleles for type 2 diabetes with prediabetes accounting for age, anthropometry, inflammatory markers and lifestyle habits.

DESIGN

Cross-sectional study of 129 men and 157 women of medium-sized companies in northern Germany in the Delay of Impaired Glucose Tolerance by a Healthy Lifestyle Trial (DELIGHT).

METHODS

Besides established risk factors, 41 single nucleotide polymorphisms (SNPs) that have previously been found to be associated with type 2 diabetes were analyzed. As a nonparametric test a random forest approach was used that allows processing of a large number of predictors. Variables with the highest impact were entered into a multivariate logistic regression model to estimate their association with prediabetes.

RESULTS

Individuals with prediabetes were characterized by a slightly, but significantly higher number of type 2 diabetes risk alleles (42.5±4.1 vs. 41.3±4.1, p = 0.013). After adjustment for age and waist circumference 6 SNPs with the highest impact in the random forest analysis were associated with risk for prediabetes in a logistic regression model. At least 5 of these SNPs were positively related to prediabetic status (odds ratio for prediabetes 1.57 per allele (Cl 1.21-2.10, p = 0.001)).

CONCLUSIONS

This explorative analysis of data of DELIGHT demonstrates that at least 6 out of 41 genetic variants characteristic of individuals with type 2 diabetes may also be associated with prediabetes. Accumulation of these risk alleles may markedly increase the risk for prediabetes. However, prospective studies are required to corroborate these findings and to demonstrate the predictive value of these genetic variants for the risk to develop prediabetes.