Type 2 diabetes whole-genome association study in four populations: the DiaGen consortium

Novel Risk Variants in the Oxytocin Receptor Gene (OXTR) Possibly Linked to and Associated with Familial Type 2 Diabetes

The oxytocin system is well-known for its role in social bonding and reproduction. Recently, the oxytocin system was found to play other metabolic roles such as regulation of food intake, peripheral glucose uptake, and insulin sensitivity. Variants in OXTR gene have been associated with overeating, increased cardiovascular risk, and type 2 diabetes (T2D). We tested 20 microarray-derived single nucleotide polymorphisms in the OXTR gene in 212 Italian families with rich family history for T2D and found four novel and one previously reported variant suggestively significant for linkage and association with the risk of T2D. Our study has shed some light into the genetics of susceptibility to T2D at least in Italian families.

Association between TCF7L2 polymorphism and type 2 diabetes mellitus susceptibility: a case-control study among the Bangladeshi population

BACKGROUND

Diabetes is a severe health burden for Bangladesh. Genetic polymorphism has been reported to be one of the major risk factors for diabetes in various studies. TCF7L2 (transcription factor 7 like 2) transcripts in the human β-cell have effects on β-cell survival, function, and Wnt signaling activation. This study aimed to evaluate the frequency and association of various polymorphisms namely TCF7L2 rs12255372 and rs7903146 among Bangladeshi patients with T2DM (Type 2 Diabetes Mellitus).

METHODS

This case-control study included 300 patients with T2DM and 234 healthy individuals from two health facilities in the Chattogram Division of Bangladesh. Anthropometric measurements were assessed using a self-reported, structured, eight-item questionnaire. The polymorphisms were identified by PCR-RFLP and sequencing method.

RESULTS

A strong association of T2DM with polymorphisms was observed, including rs12255372 (p = 0.0004) and rs7903146 (p = 0.005). It was observed that the risk genotype at rs12255372 was associated with age (p = 0.009), a family history of diabetes (p < 0.0001), and HbA1C (p < 0.0001). Furthermore, it was found that rs12255372 was substantially associated with hypertension (p = 0.03), eye problems (p = 0.01), and neurological abnormalities (p = 0.02).

CONCLUSION

This study postulates that TCF7L2 genetic polymorphism is associated with the risk of T2DM among the studied Bangladeshi population. The findings should be replicated through more studies with a large number of samples and in different populations.

Variants of SLC2A10 may be Linked to Poor Response to Metformin

Purpose

A study among Filipinos revealed that only 15% of patients with diabetes achieved glycemic control, and poor response to metformin could be one of the possible reasons. Recent studies demonstrate how genetic variations influence response to metformin. Hence, the present study aimed to determine genetic variants associated with poor response to metformin.

Methods

Using a candidate variant approach, 195 adult Filipino participants with newly diagnosed type 2 diabetes mellitus (T2DM) were enrolled in a case-control study. Genomic DNA from blood samples were collected. Allelic and genotypic associations of variants with poor response to metformin were determined using exact statistical methods.

Results

Several polymorphisms were nominally associated with poor response to metformin (P_uncorr < 0.05). The most notable is the association of multiple variants in the SLC2A10 gene—rs2425911, rs3092412, and rs2425904—with common additive genetic mode of inheritance. Other variants that have possible associations with poor drug response include rs340874 (PROX-AS1), rs815815 (CALM2), rs1333049 (CDKN2B-AS1), rs2010963 (VEGFA), rs1535435 and rs9494266 (AHI1), rs11128347 (PDZRN3), rs1805081 (NPC1), and rs13266634 (SLC30A8).

Conclusion

In Filipinos, a trend for the association for several variants was noted, with further observation that several mechanisms may be involved. The results may serve as pilot data for further validation of candidate variants for T2DM pharmacotherapy.

Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome

STUDY QUESTION

Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe?

SUMMARY ANSWER

We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 (CHEK2) gene and a third in myosin X (MYO10).

WHAT IS KNOWN ALREADY

PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects.

STUDY DESIGN, SIZE, DURATION

A population-based case-control GWAS was carried out.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case-control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts.

MAIN RESULTS AND THE ROLE OF CHANCE

Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 (P = 3.6×10-8, odds ratio (OR) = 3.01 [2.02-4.50] minor allele frequency (MAF) = 0.005) and rs182075939 (P = 1.9×10-16, OR = 1.69 [1.49-1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC (r2 = 0.95) and a missense I157T (r2 = 0.83) in CHEK2. The third novel association is a common variant near MYO10 (rs9312937, P = 1.7 × 10-8, OR = 1.16 [1.10-1.23], MAF = 0.44). We also replicated four previous reported associations near the genes Erb-B2 Receptor Tyrosine Kinase 4 (ERBB4), DENN Domain Containing 1A (DENND1A), FSH Subunit Beta (FSHB) and Zinc Finger And BTB Domain Containing 16 (ZBTB16). When adding BMI as a covariate only one of the novel variants remained genome-wide significant in the meta-analysis (the EstBB lead signal in CHEK2 rs182075939, P = 1.9×10-16, OR = 1.74 [1.5-2.01]) possibly owing to reduced sample size.

LARGE SCALE DATA

The age- and BMI-adjusted GWAS meta-analysis summary statistics are available for download from the GWAS Catalog with accession numbers GCST90044902 and GCST90044903.

LIMITATIONS, REASONS FOR CAUTION

The main limitation was the low prevalence of PCOS in registers; however, the ones with the diagnosis most likely represent the most severe cases. Also, BMI data were not available for all (63% for FinnGen, 76% for EstBB), and the biobank setting limited the accessibility of PCOS phenotypes and laboratory values.

WIDER IMPLICATIONS OF THE FINDINGS

This study encourages the use of isolated populations to perform genetic association studies for the identification of rare variants contributing to the genetic landscape of complex diseases such as PCOS.

STUDY FUNDING/COMPETING INTEREST(S)

This work has received funding from the European Union's Horizon 2020 research and innovation programme under the MATER Marie Skłodowska-Curie grant agreement No. 813707 (N.P.-G., T.L., T.P.), the Estonian Research Council grant (PRG687, T.L.), the Academy of Finland grants 315921 (T.P.), 321763 (T.P.), 297338 (J.K.), 307247 (J.K.), 344695 (H.L.), Novo Nordisk Foundation grant NNF17OC0026062 (J.K.), the Sigrid Juselius Foundation project grants (T.L., J.K., T.P.), Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.). The funders had no role in study design, data collection and analysis, publishing or preparation of the manuscript. The authors declare no conflicts of interest.

Marine Algae-Derived Bioactive Compounds: A New Wave of Nanodrugs?

Marine algae are rich in bioactive nutraceuticals (e.g., carbohydrates, proteins, minerals, fatty acids, antioxidants, and pigments). Biotic (e.g., plants, microorganisms) and abiotic factors (e.g., temperature, pH, salinity, light intensity) contribute to the production of primary and secondary metabolites by algae. Easy, profitable, and sustainable recovery methods include novel solid-liquid and liquid-liquid extraction techniques (e.g., supercritical, high pressure, microwave, ultrasound, enzymatic). The spectacular findings of algal-mediated synthesis of nanotheranostics has attracted further interest because of the availability of microalgae-based natural bioactive therapeutic compounds and the cost-effective commercialization of stable microalgal drugs. Algal extracts can serve as stabilizing/capping and reducing agents for the synthesis of thermodynamically stable nanoparticles (NPs). Different types of nanotherapeutics have been synthesized using physical, chemical, and biological methods. Marine algae are a fascinating source of lead theranostics compounds, and the development of nanotheranostics has been linked to enhanced drug efficacy and safety. Indeed, algae are remarkable nanobiofactories, and their pragmatic properties reside in their (i) ease of handling; (ii) capacity to absorb/accumulate inorganic metallic ions; (iii) cost-effectiveness; and (iv) capacity of eco-friendly, rapid, and healthier synthesis of NPs. Preclinical and clinical trials shall enable to really define effective algal-based nanotherapies. This review aims to provide an overview of the main algal compounds that are nutraceuticals and that can be extracted and purified for nanotheranostic purposes.

The 'Jekyll and Hyde' of Gluconeogenesis: Early Life Adversity, Later Life Stress, and Metabolic Disturbances

The physiological response to a psychological stressor broadly impacts energy metabolism. Inversely, changes in energy availability affect the physiological response to the stressor in terms of hypothalamus, pituitary adrenal axis (HPA), and sympathetic nervous system activation. Glucocorticoids, the endpoint of the HPA axis, are critical checkpoints in endocrine control of energy homeostasis and have been linked to metabolic diseases including obesity, insulin resistance, and type 2 diabetes. Glucocorticoids, through the glucocorticoid receptor, activate transcription of genes associated with glucose and lipid regulatory pathways and thereby control both physiological and pathophysiological systemic energy homeostasis. Here, we summarize the current knowledge of glucocorticoid functions in energy metabolism and systemic metabolic dysfunction, particularly focusing on glucose and lipid metabolism. There are elements in the external environment that induce lifelong changes in the HPA axis stress response and glucocorticoid levels, and the most prominent are early life adversity, or exposure to traumatic stress. We hypothesise that when the HPA axis is so disturbed after early life adversity, it will fundamentally alter hepatic gluconeogenesis, inducing hyperglycaemia, and hence crystalise the significant lifelong risk of developing either the metabolic syndrome, or type 2 diabetes. This gives a “Jekyll and Hyde” role to gluconeogenesis, providing the necessary energy in situations of acute stress, but driving towards pathophysiological consequences when the HPA axis has been altered.

Association of type 2 diabetes mellitus and periodontal disease susceptibility with genome-wide association-identified risk variants in a Southeastern Brazilian population

OBJECTIVE

Genome-wide association studies (GWAS) and literature have identified polymorphisms in the KCNJ11, HNF1A, IRS1, TCF7L2, CDKAL1, CDKN2B, RPSAP52, GPR45 HHEX, IL18, and RUNX2 genes associated with type 2 diabetes mellitus (T2DM) and/or periodontitis (P) in diverse populations, and we sought to evaluate them as genetic risk variants for these diseases in the Brazilian population.

MATERIAL AND METHODS

Periodontal, glycemic, and lipid data were obtained from 931 individuals divided into: control (n = 334), periodontitis (P; n = 358), and periodontitis associated with T2DM (P + T2DM; n = 239). After genotyping, associations between polymorphisms and pathologies were tested by multiple logistic and linear regressions, adjusting for age, sex, and smoking habits.

RESULTS

Considering the studied subjects, the increased risk to develop periodontitis in the periodontitis P + T2DM group was found for HNF1A-rs7957197-TA, CDKAL1-rs7754840-CG, RPSAP52-rs1531343-GC, TCF7L2-rs7903146-TT, and CDKN2B-rs7018475-GG. The association of these genetic variants for TCF7L2 and CDKN2B was confirmed for female, never smokers, and poorly controlled P + T2DM. CDKN2B-rs7018475 was associated with worse glycemic condition and periodontal parameters.

CONCLUSION

These five reported genetic variants were associated in the studied Southeastern Brazilian population as genetic risk variants of periodontitis and T2DM associated to periodontitis as comorbidity. Gene-phenotype associations with sex and smoking habits and the CDKN2B-rs7018475 with the poor glycemic control and more severe periodontal conditions should be further investigated.

CLINICAL RELEVANCE

Polymorphisms in the CDKAL1-rs7754840, HNF1A-rs7957197, RPSAP52-rs1531343, TCF7L2-rs7903146, and CDKN2B-rs7018475 might predispose to periodontitis and T2DM associated with periodontitis. These findings may be useful in public health genomics and future advanced clinical practice, since genetic carriage can be measured before disease onset, being of potential great benefit for treatment planning and prognosis in early disease stages.

The COVID-19 Pandemic: Does Our Early Life Environment, Life Trajectory and Socioeconomic Status Determine Disease Susceptibility and Severity?

A poor socioeconomic environment and social adversity are fundamental determinants of human life span, well-being and health. Previous influenza pandemics showed that socioeconomic factors may determine both disease detection rates and overall outcomes, and preliminary data from the ongoing coronavirus disease (COVID-19) pandemic suggests that this is still true. Over the past years it has become clear that early-life adversity (ELA) plays a critical role biasing the immune system towards a pro-inflammatory and senescent phenotype many years later. Cytotoxic T-lymphocytes (CTL) appear to be particularly sensitive to the early life social environment. As we understand more about the immune response to SARS-CoV-2 it appears that a functional CTL (CD8+) response is required to clear the infection and COVID-19 severity is increased as the CD8+ response becomes somehow diminished or exhausted. This raises the hypothesis that the ELA-induced pro-inflammatory and senescent phenotype may play a role in determining the clinical course of COVID-19, and the convergence of ELA-induced senescence and COVID-19 induced exhaustion represents the worst-case scenario with the least effective T-cell response. If the correct data is collected, it may be possible to separate the early life elements that have made people particularly vulnerable to COVID-19 many years later. This will, naturally, then help us identify those that are most at risk from developing the severest forms of COVID-19. In order to do this, we need to recognize socioeconomic and early-life factors as genuine medically and clinically relevant data that urgently need to be collected. Finally, many biological samples have been collected in the ongoing studies. The mechanisms linking the early life environment with a defined later-life phenotype are starting to be elucidated, and perhaps hold the key to understanding inequalities and differences in the severity of COVID-19.

Characterization of Signaling Pathways Associated with Pancreatic β-cell Adaptive Flexibility in Compensation of Obesity-linked Diabetes in db/db Mice

The onset of obesity-linked type 2 diabetes (T2D) is marked by an eventual failure in pancreatic β-cell function and mass that is no longer able to compensate for the inherent insulin resistance and increased metabolic load intrinsic to obesity. However, in a commonly used model of T2D, the db/db mouse, β-cells have an inbuilt adaptive flexibility enabling them to effectively adjust insulin production rates relative to the metabolic demand. Pancreatic β-cells from these animals have markedly reduced intracellular insulin stores, yet high rates of (pro)insulin secretion, together with a substantial increase in proinsulin biosynthesis highlighted by expanded rough endoplasmic reticulum and Golgi apparatus. However, when the metabolic overload and/or hyperglycemia is normalized, β-cells from db/db mice quickly restore their insulin stores and normalize secretory function. This demonstrates the β-cell's adaptive flexibility and indicates that therapeutic approaches applied to encourage β-cell rest are capable of restoring endogenous β-cell function. However, mechanisms that regulate β-cell adaptive flexibility are essentially unknown. To gain deeper mechanistic insight into the molecular events underlying β-cell adaptive flexibility in db/db β-cells, we conducted a combined proteomic and post-translational modification specific proteomic (PTMomics) approach on islets from db/db mice and wild-type controls (WT) with or without prior exposure to normal glucose levels. We identified differential modifications of proteins involved in redox homeostasis, protein refolding, K48-linked deubiquitination, mRNA/protein export, focal adhesion, ERK1/2 signaling, and renin-angiotensin-aldosterone signaling, as well as sialyltransferase activity, associated with β-cell adaptive flexibility. These proteins are all related to proinsulin biosynthesis and processing, maturation of insulin secretory granules, and vesicular trafficking-core pathways involved in the adaptation of insulin production to meet metabolic demand. Collectively, this study outlines a novel and comprehensive global PTMome signaling map that highlights important molecular mechanisms related to the adaptive flexibility of β-cell function, providing improved insight into disease pathogenesis of T2D.

Interrelationship of the rs7903146 TCF7L2 gene variant with measures of glucose metabolism and adiposity: The NEO study

BACKGROUND AND AIMS

We investigated the interrelationship of rs7903146-T in TCF7L2 with measures of glucose metabolism and measures of adiposity.

METHODS AND RESULTS

This cross-sectional analysis was conducted in 5744 middle-aged participants (mean (standard deviation [SD]) age is 55.9 (6.0) years) from the Netherlands Epidemiology of Obesity (NEO) Study. Associations between rs7903146-T and Type 2 diabetes mellitus (T2D) were assessed with logistic regression. Additive (per-allele) associations with measures of glucose metabolism (e.g., fasting insulin) and adiposity (e.g., body mass index [BMI]) were examined with multivariable linear regression. In the total study population, rs7903146-T was associated with a higher risk of T2D (additive odds ratio: 1.42; 95% confidence interval: 1.17; 1.72), and specifically with T2D treated with insulin analogs (2.31 [1.19; 4.46]). After exclusion of participants treated with glucose-lowering medication, rs7903146-T was associated with lower mean insulin concentration (additive mean difference: -0.07 SD [-0.14; 0.00]), but not with higher mean glucose concentration (0.03 SD [-0.01; 0.07]). Furthermore, rs7903146-T was associated with, among other measures of adiposity, a lower mean BMI (-0.04 SD [-0.09; -0.00]), and a lower mean total body fat (-0.04 SD [-0.08; -0.00]). The association between rs7903146-T and T2D increased after adjustment for BMI (odds ratio: 1.51 [1.24; 1.86]); the association between rs7903146-T and fasting insulin diminished after adjustment (-0.05 SD [-0.11; 0.02]).

CONCLUSION

rs7903146-T is associated with a decreased insulin concentration and increased risk of T2D with opposing effects of adjustment for adiposity.

Type 2 Diabetes Mellitus and Cardiovascular Disease: Genetic and Epigenetic Links

Type 2 diabetes mellitus (DM) is a common metabolic disorder predisposing to diabetic cardiomyopathy and atherosclerotic cardiovascular disease (CVD), which could lead to heart failure through a variety of mechanisms, including myocardial infarction and chronic pressure overload. Pathogenetic mechanisms, mainly linked to hyperglycemia and chronic sustained hyperinsulinemia, include changes in metabolic profiles, intracellular signaling pathways, energy production, redox status, increased susceptibility to ischemia, and extracellular matrix remodeling. The close relationship between type 2 DM and CVD has led to the common soil hypothesis, postulating that both conditions share common genetic and environmental factors influencing this association. However, although the common risk factors of both CVD and type 2 DM, such as obesity, insulin resistance, dyslipidemia, inflammation, and thrombophilia, can be identified in the majority of affected patients, less is known about how these factors influence both conditions, so that efforts are still needed for a more comprehensive understanding of this relationship. The genetic, epigenetic, and environmental backgrounds of both type 2 DM and CVD have been more recently studied and updated. However, the underlying pathogenetic mechanisms have seldom been investigated within the broader shared background, but rather studied in the specific context of type 2 DM or CVD, separately. As the precise pathophysiological links between type 2 DM and CVD are not entirely understood and many aspects still require elucidation, an integrated description of the genetic, epigenetic, and environmental influences involved in the concomitant development of both diseases is of paramount importance to shed new light on the interlinks between type 2 DM and CVD. This review addresses the current knowledge of overlapping genetic and epigenetic aspects in type 2 DM and CVD, including microRNAs and long non-coding RNAs, whose abnormal regulation has been implicated in both disease conditions, either etiologically or as cause for their progression. Understanding the links between these disorders may help to drive future research toward an integrated pathophysiological approach and to provide future directions in the field.

PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies

Genome-wide, imputed, sequence, and structural data are now available for exceedingly large sample sizes. The needs for data management, handling population structure and related samples, and performing associations have largely been met. However, the infrastructure to support analyses involving complexity beyond genome-wide association studies is not standardized or centralized. We provide the PLatform for the Analysis, Translation, and Organization of large-scale data (PLATO), a software tool equipped to handle multi-omic data for hundreds of thousands of samples to explore complexity using genetic interactions, environment-wide association studies and gene–environment interactions, phenome-wide association studies, as well as copy number and rare variant analyses. Using the data from the Marshfield Personalized Medicine Research Project, a site in the electronic Medical Records and Genomics Network, we apply each feature of PLATO to type 2 diabetes and demonstrate how PLATO can be used to uncover the complex etiology of common traits.

Centralized infrastructure to support analyses involving complexity beyond genome-wide association studies is broadly needed. Here, Ritchie and colleagues develop PLATO, a software tool to process and integrate various methods for this task.

LncRNAs: key players and novel insights into diabetes mellitus

Long non-coding RNAs (LncRNAs) are a class of endogenous RNA molecules, which have a transcribing length of over 200 nt, lack a complete functional open reading frame (ORF), and rarely encode a functional short peptide. Recent studies have revealed that disruption of LncRNAs levels correlates with several human diseases, including diabetes mellitus (DM), a complex multifactorial metabolic disorder affecting more than 400 million people worldwide. LncRNAs are emerging as pivotal regulators in various biological processes, in the progression of DM and its associated complications, involving pancreatic β-cell disorder, insulin resistance, and epigenetic regulation, etc. Further investigation into the mechanisms of action of LncRNAs in DM will be of great value in the thorough understanding of pathogenesis. However, prior to successful application of LncRNAs, further search for molecular biomarkers and drug targets to provide a new strategy for DM prevention, early diagnosis, and therapy is warranted.

Association of polymorphic markers of genes FTO, KCNJ11, CDKAL1, SLC30A8, and CDKN2B with type 2 diabetes mellitus in the Russian population

Background

The association of type 2 diabetes mellitus (T2DM) with the KCNJ11, CDKAL1, SLC30A8, CDKN2B, and FTO genes in the Russian population has not been well studied. In this study, we analysed the population frequencies of polymorphic markers of these genes.

Methods

The study included 862 patients with T2DM and 443 control subjects of Russian origin. All subjects were genotyped for 10 single nucleotide polymorphisms (SNPs) of the genes using real-time PCR (TaqMan assays). HOMA-IR and HOMA-β were used to measure insulin resistance and β-cell secretory function, respectively.

Results

The analysis of the frequency distribution of polymorphic markers for genes KCNJ11, CDKAL1, SLC30A8 and CDKN2B showed statistically significant associations with T2DM in the Russian population. The association between the FTO gene and T2DM was not statistically significant. The polymorphic markers rs5219 of the KCNJ11 gene, rs13266634 of the SLC30A8 gene, rs10811661 of the CDKN2B gene and rs9465871, rs7756992 and rs10946398 of the CDKAL1 gene showed a significant association with impaired glucose metabolism or impaired β-cell function.

Conclusion

In the Russian population, genes, which affect insulin synthesis and secretion in the β-cells of the pancreas, play a central role in the development of T2DM.

Utilization of genetic data can improve the prediction of type 2 diabetes incidence in a Swedish cohort

The aim of this study was to measure the impact of genetic data in improving the prediction of type 2 diabetes (T2D) in the Malmö Diet and Cancer Study cohort. The current study was performed in 3,426 Swedish individuals and utilizes of a set of genetic and environmental risk data. We first validated our environmental risk model by comparing it to both the Finnish Diabetes Risk Score and the T2D risk model derived from the Framingham Offspring Study. The area under the curve (AUC) for our environmental model was 0.72 [95% CI, 0.69–0.74], which was significantly better than both the Finnish (0.64 [95% CI, 0.61–0.66], p-value < 1 x 10⁻⁴) and Framingham (0.69 [95% CI, 0.66–0.71], p-value = 0.0017) risk scores. We then verified that the genetic data has a statistically significant positive correlation with incidence of T2D in the studied population. We also verified that adding genetic data slightly but statistically increased the AUC of a model based only on environmental risk factors (RFs, AUC shift +1.0% from 0.72 to 0.73, p-value = 0.042). To study the dependence of the results on the environmental RFs, we divided the population into two equally sized risk groups based only on their environmental risk and repeated the same analysis within each subpopulation. While there is a statistically significant positive correlation between the genetic data and incidence of T2D in both environmental risk categories, the positive shift in the AUC remains statistically significant only in the category with the lower environmental risk. These results demonstrate that genetic data can be used to increase the accuracy of T2D prediction. Also, the data suggests that genetic data is more valuable in improving T2D prediction in populations with lower environmental risk. This suggests that the impact of genetic data depends on the environmental risk of the studied population and thus genetic association studies should be performed in light of the underlying environmental risk of the population.

Revealing allele-specific gene expression by single-cell transcriptomics

Single-cell sequencing has emerged as a revolutionary method that reveals biological processes with unprecedented resolution and scale, and has already greatly impacted biology and medicine. To investigate processes such as alternative splicing, novel exon detection and allele-specific expression (ASE), full-length based single-cell RNA-seq methods are required for broad sequence coverage and single nucleotide polymorphism (SNP) identification. In this review, we revisit recent achievements from studies that used single-cell RNA-seq to advance our understanding of ASE in the context of both autosomal and X-chromosome genes. We also recapitulate useful bioinformatic tools developed to identify haplotype phase.

Single nucleotide polymorphisms in an Indian cohort and association of CNTN4, MMP2 and SNTB1 variants with oral cancer

Oral cancer is a high incidence cancer in India primarily due to the prevalent tobacco/areca nut chewing habits and hence a major health concern. India constitutes 26% of the global oral cancer burden. Besides the well-established risk factors, the genomic constitution of an individual plays a role in oral cancer. The aim of the current study was to analyse genomic variants represented as single nucleotide polymorphisms (SNPs), analyse their prevalence and investigate risk association of allelotypes/genotypes to oral cancers. Eleven SNPs in genes associated with biological functions were analysed in an Indian cohort (n = 1000) comprising 500 oral cancer patients and 500 long term tobacco habitués as controls, using Allelic discrimination Real-Time PCR assay with SYBR Green dye. Fisher's exact test and Odds Ratio were used for statistical analysis. Increased risk was observed for rs9849237 CC [P = 0.008; OR 1.412 (1.09-1.82)] and rs243865 CT [P = 0.004; OR 1.469 (1.13-1.90)] genotypes, whereas rs9849237 CT [P = 0.034; OR 0.755 (0.58-0.97)], rs243865 CC [P = 0.002; OR 0.669 (0.51-0.86)] and rs10090787 CC [P = 0.049; OR 0.774 (0.60-0.99)] genotypes indicated decreased risk to oral cancer. The other SNPs showed equidistribution in both groups. Our data indicated genotypes and alleles in specific SNPs rs9849237, rs243865 and rs10090787 with increased/decreased risk to oral cancer.

Replication of KCNJ11 (p.E23K) and ABCC8 (p.S1369A) Association in Russian Diabetes Mellitus 2 Type Cohort and Meta-Analysis

The genes ABCC8 and KCNJ11 have received intense focus in type 2 diabetes mellitus (T2DM) research over the past two decades. It has been hypothesized that the p.E23K (KCNJ11) mutation in the 11p15.1 region may play an important role in the development of T2DM. In 2009, Hamming et al. found that the p.1369A (ABCC8) variant may be a causal factor in the disease; therefore, in this study we performed a meta-analysis to evaluate the association between these single nucleotide polymorphisms (SNPs), including our original data on the Siberian population (1384 T2DM and 414 controls). We found rs5219 and rs757110 were not associated with T2DM in this population, and that there was linkage disequilibrium in Siberians (D’=0.766, r²= 0.5633). In addition, the haplotype rs757110[T]-rs5219[C] (p.23K/p.S1369) was associated with T2DM (OR = 1.52, 95% CI: 1.04-2.24). We included 44 original studies published by June 2014 in a meta-analysis of the p.E23K association with T2DM. The total OR was 1.14 (95% CI: 1.11-1.17) for p.E23K for a total sample size of 137,298. For p.S1369A, a meta-analysis was conducted on a total of 10 studies with a total sample size of 14,136 and pooled OR of 1.14 [95% CI (1.08-1.19); p = 2 x 10^-6]. Our calculations identified causal genetic variation within the ABCC8/KCNJ11 region for T2DM with an OR of approximately 1.15 in Caucasians and Asians. Moreover, the OR value was not dependent on the frequency of p.E23K or p.S1369A in the populations.

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.

Beta cell connectivity in pancreatic islets: a type 2 diabetes target?

Beta cell connectivity describes the phenomenon whereby the islet context improves insulin secretion by providing a three-dimensional platform for intercellular signaling processes. Thus, the precise flow of information through homotypically interconnected beta cells leads to the large-scale organization of hormone release activities, influencing cell responses to glucose and other secretagogues. Although a phenomenon whose importance has arguably been underappreciated in islet biology until recently, a growing number of studies suggest that such cell-cell communication is a fundamental property of this micro-organ. Hence, connectivity may plausibly be targeted by both environmental and genetic factors in type 2 diabetes mellitus (T2DM) to perturb normal beta cell function and insulin release. Here, we review the mechanisms that contribute to beta cell connectivity, discuss how these may fail during T2DM, and examine approaches to restore insulin secretion by boosting cell communication.

Cumulative effect and predictive value of genetic variants associated with type 2 diabetes in Han Chinese: a case-control study

Background

Genome-wide association studies (GWAS) have identified dozens of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes risk. We have previously confirmed the associations of genetic variants in HHEX, CDKAL1, VEGFA and FTO with type 2 diabetes in Han Chinese. However, the cumulative effect and predictive value of these GWAS identified SNPs on the risk of type 2 diabetes in Han Chinese are largely unknown.

Methodology/Principal Findings

We conducted a two-stage case-control study consisting of 2,925 cases and 3,281controls to examine the association of 30 SNPs identified by GWAS with type 2 diabetes in Han Chinese. Significant associations were found for proxy SNPs at KCNQ1 [odds ratio (OR) = 1.41, P = 9.91 × 10–16 for rs2237897], CDKN2A/CDKN2B (OR = 1.30, P = 1.34 × 10–10 for rs10811661), CENTD2 (OR = 1.28, P = 9.88 × 10-4 for rs1552224) and SLC30A8 (OR = 1.19, P = 1.43 × 10-5 for rs13266634). We further evaluated the cumulative effect on type 2 diabetes of these 4 SNPs, in combination with 5 SNPs at HHEX, CDKAL1, VEGFA and FTO reported previously. Individuals carrying 12 or more risk alleles had a nearly 4-fold increased risk for developing type 2 diabetes compared with those carrying less than 6 risk alleles [adjusted OR = 3.68, 95% confidence interval (CI): 2.76–4.91]. Adding the genetic factors to clinical factors slightly improved the prediction of type 2 diabetes, with the area under the receiver operating characteristic curve increasing from 0.76 to 0.78. However, the difference was statistically significant (P < 0.0001).

Conclusions/Significance

We confirmed associations of SNPs in KCNQ1, CDKN2A/CDKN2B, CENTD2 and SLC30A8 with type 2 diabetes in Han Chinese. The utilization of genetic information may improve the accuracy of risk prediction in combination with clinical characteristics for type 2 diabetes.

Global Gene Expression Profiling in Omental Adipose Tissue of Morbidly Obese Diabetic African Americans

BACKGROUND

Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D.

METHODS

Twenty morbidly obese (mean BMI: about 54 kg/m²) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals.

RESULTS

At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase (HNRNPA1, TNKS2), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified.

CONCLUSION

This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.

Inhibition of secreted frizzled-related protein 5 improves glucose metabolism

Elucidating the role of secreted frizzled-related protein 5 (SFRP5) in metabolism and obesity has been complicated by contradictory findings when knockout mice were used to determine metabolic phenotypes. By overexpressing SFRP5 in obese, prediabetic mice we consistently observed elevated hyperglycemia and glucose intolerance, supporting SFRP5 as a negative regulator of glucose metabolism. Accordingly, Sfrp5 mRNA expression analysis of both epididymal and subcutaneous adipose depots of mice indicated a correlation with obesity. Thus, we generated a monoclonal antibody (mAb) against SFRP5 to ascertain the effect of SFRP5 inhibition in vivo. Congruent with SFRP5 overexpression worsening blood glucose levels and glucose intolerance, anti-SFRP5 mAb therapy improved these phenotypes in vivo. The results from both the overexpression and mAb inhibition studies suggest a role for SFRP5 in glucose metabolism and pancreatic β-cell function and thus establish the use of an anti-SFRP5 mAb as a potential approach to treat type 2 diabetes.

Genomic assortative mating in marriages in the United States

Assortative mating in phenotype in human marriages has been widely observed. Using genome-wide genotype data from the Framingham Heart study (FHS; number of married couples = 989) and Health Retirement Survey (HRS; number of married couples = 3,474), this study investigates genomic assortative mating in human marriages. Two types of genomic marital correlations are calculated. The first is a correlation specific to a single married couple "averaged" over all available autosomal single-nucleotide polymorphism (SNPs). In FHS, the average married-couple correlation is 0.0018 with p = 3 × 10(-5); in HRS, it is 0.0017 with p = 7.13 × 10(-13). The marital correlation among the positively assorting SNPs is 0.001 (p = .0043) in FHS and 0.015 (p = 1.66 × 10(-24)) in HRS. The sizes of these estimates in FHS and HRS are consistent with what are suggested by the distribution of the allelic combination. The study also estimated SNP-specific correlation "averaged" over all married couples. Suggestive evidence is reported. Future studies need to consider a more general form of genomic assortment, in which different allelic forms in homologous genes and non-homologous genes result in the same phenotype.

Genetic association study with metabolic syndrome and metabolic-related traits in a cross-sectional sample and a 10-year longitudinal sample of chinese elderly population

Background

The metabolic syndrome (MetS) has been known as partly heritable, while the number of genetic studies on MetS and metabolic-related traits among Chinese elderly was limited.

Methods

A cross-sectional analysis was performed among 2 014 aged participants from September 2009 to June 2010 in Beijing, China. An additional longitudinal study was carried out among the same study population from 2001 to 2010. Biochemical profile and anthropometric parameters of all the participants were measured. The associations of 23 SNPs located within 17 candidate genes (MTHFR, PPARγ, LPL, INSIG, TCF7L2, FTO, KCNJ11, JAZF1, CDKN2A/B, ADIPOQ, WFS1, CDKAL1, IGF2BP2, KCNQ1, MTNR1B, IRS1, ACE) with overweight and obesity, diabetes, metabolic phenotypes, and MetS were examined in both studies.

Results

In this Chinese elderly population, prevalence of overweight, central obesity, diabetes, dyslipidemia, hypertension, and MetS were 48.3%, 71.0%, 32.4%, 75.7%, 68.3% and 54.5%, respectively. In the cross-sectional analyses, no SNP was found to be associated with MetS. Genotype TT of SNP rs4402960 within the gene IGF2BP2 was associated with overweight (odds ratio (OR)  = 0.479, 95% confidence interval (CI): 0.316-0.724, p = 0.001) and genotype CA of SNP rs1801131 within the gene MTHFR was associated with hypertension (OR = 1.560, 95% CI: 1.194–2.240, p = 0.001). However, these associations were not observed in the longitudinal analyses.

Conclusions

The associations of SNP rs4402960 with overweight as well as the association of SNP rs1801131 with hypertension were found to be statistically significant. No SNP was identified to be associated with MetS in our study with statistical significance.

Cross-sectional and longitudinal replication analyses of genome-wide association loci of type 2 diabetes in Han Chinese

This study aimed to examine genomic loci of type 2 diabetes (T2D) initially identified by genome-wide association studies in populations of European ancestry for their associations with T2D and quantitative glycemic traits, as well as their effects on longitudinal change in fasting plasma glucose (FPG) and T2D development, in the Chinese population. Single nucleotide polymorphisms (SNP) from 25 loci were genotyped in a large case-control sample of 10,001 subjects (5,338 T2D cases and 4,663 controls) and a prospective cohort of 1,881 Chinese. In the case-control sample, 8 SNPs in or near WFS1, CDKAL1, CDKN2A/2B, CDC123, HHEX, TCF7L2, KCNQ1, and MTNR1B were significantly associated with T2D (P<0.05). Thirteen SNPs were associated with quantitative glycemic traits. For example, the most significant SNP, rs10811661 near CDKN2A/2B (P = 1.11×10⁻⁸ for T2D), was also associated with 2-h glucose level of an oral glucose tolerance test (P = 9.11×10⁻³) and insulinogenic index (P = 2.71×10⁻²). In the cohort study, individuals carrying more risk alleles of the replicated SNPs had greater FPG increase and T2D incidence in a 7.5-year follow-up period, with each quartile increase in the number of risk alleles being associated with a 0.06 mmol/l greater increase in FPG (P = 0.03) and 19% higher odds of developing T2D (P = 0.058). Our study identified the associations of several established T2D-loci in Europeans with T2D and quantitative glycemic traits in the Chinese population. The prospective data also suggest their potential role in the risk prediction of T2D in the Chinese population.

Overlap of genetic susceptibility to type 1 diabetes, type 2 diabetes, and latent autoimmune diabetes in adults

Despite the notion that there is a degree of commonality to the biological etiology of type 1 diabetes (T1D) and type 2 diabetes (T2D), the lack of overlap in the genetic factors underpinning each of them suggests very distinct mechanisms. A disorder considered to be at the "intersection" of these two diseases is "latent autoimmune diabetes in adults" (LADA). Interestingly, genetic signals from both T1D and T2D are also seen in LADA, including the key HLA and transcription factor 7-like 2 (TCF7L2) loci, but the magnitudes of these effects are more complex than just pointing to LADA as being a simple admixture of T1D and T2D. We review the current status of the understanding of the genetics of LADA and place it in the context of what is known about the genetics of its better-studied "cousins," T1D and T2D, especially with respect to the myriad of discoveries made over the last decade through genome-wide association studies.

The architecture of risk for type 2 diabetes: understanding Asia in the context of global findings

The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk.

Putative association between UBE2E2 polymorphisms and the risk of gestational diabetes mellitus

We hypothesized that ubiquitin-conjugating enzyme E2 E2 (UBE2E2) may be associated with gestational diabetes mellitus (GDM) and conducted association analyses. A total of 2071 subjects were recruited for the study, with 1104 cases and 967 controls. Two UBE2E2 single-nucleotide polymorphisms rs6780569 and rs7612463, and their haplotypes were analyzed for the study. As a result, rs7612463 showed a significant association with GDM in the recessive model. In addition, the regression analyses for the phenotypes showed that rs6780569. rs7612463 and ht2 showed significant associations with fasting plasma glucose (FPG) in recessive models, while ht1 showed an association in the dominant model. Our results show that the genetic variants of UBE2E2 are associated with GDM and FPG, which could be an important preliminary result for future studies.

Association between TCF7L2 gene polymorphism and cancer risk: a meta-analysis

Objective

The transcription factor 7-like 2 (TCF7L2) gene has been suggested to play an important role in the pathogenesis of cancer. However, the results have been inconsistent. In this study, we performed a meta-analysis to clarify the associations between TCF7L2 polymorphism and cancer risk.

Methods

Published literature from PubMed and EMBASE were retrieved. Pooled odds ratios (ORs) with 95% confidence interval (CIs) were calculated using fixed- or random-effects model.

Results

A total of 19 studies (14,814 cases and 33,856 controls) were identified for the analysis of the association between TCF7L2 polymorphism and cancer risk. The results showed that TCF7L2 polymorphism was associated with breast cancer (Homogeneous model: OR = 1.17, 95%CI = 1.02–1.35, I² = 21.8%, p for heterogeneity = 0.276; Heterogeneous model: OR = 1.11, 95%CI = 1.03–1.20, I² = 0.0%, p for heterogeneity = 0.543), prostate cancer (Homogeneous model: OR = 0.89, 95%CI = 0.84–0.96, I² = 0.0%, p for heterogeneity = 0.640; Heterogeneous model: OR = 0.89, 95%CI = 0.84–0.95, I² = 0.0%, p for heterogeneity = 0.871), and colon cancer (Heterogeneous model: OR = 1.15, 95%CI = 1.01–1.31, I² = 0.0%, p for heterogeneity = 0.658), but not with colorectal cancer, lung cancer, and ovarian cancer.

Conclusions

The present meta-analysis indicated that there were significantly associations between the TCF7L2 rs7903146 polymorphism and risk of breast, prostate and colon cancers, rather than colorectal cancer, lung cancer, and ovarian cancer.

Generation of high quality chromatin immunoprecipitation DNA template for high-throughput sequencing (ChIP-seq)

ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions. For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers. Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.

Association of TCF7L2 gene polymorphisms with T2DM in the population of Hyderabad, India

We attempt to evaluate the nature of association of TCF7L2 gene variants with T2DM, for the first time in the population of Hyderabad, which is considered to be diabetic capital of India. It is a case-control study of the three SNPs of TCF7L2, rs7903146, rs12255372 and rs11196205, genotyped on Sequenom Massarray platform, in a sample of 758 patients and 621 controls. The risk allele frequency of the three SNPs was found to be significantly higher in the T2DM cases than controls, implicating susceptibility for diabetes (p<0.01). The greatest risk of developing the disease was conferred by rs7903146. Further, the logistic regression of genotypes of each SNP under log additive model, and the haplotypes constituted by at least one of the three risk alleles also show significantly greater risk of developing T2DM when compared to the wild type haplotype. Further, BMI and WHR emerge as significant covariates with confounding effects. The strong association of the TCF7L2 SNPs with T2DM is consistent with the findings among other Indian and Non-Indian populations, suggesting universal phenomena of its association across ethnic groups globally, both within and outside the Indian subcontinent, albeit the functional relevance of these SNPs needs yet to be established.

Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.

Genetic risk factors for type 2 diabetes: a trans-regulatory genetic architecture?

To date, 68 loci have been associated with type 2 diabetes (T2D) or glucose homeostasis traits. We report here the results of experiments aimed at functionally characterizing the SNPs replicated for T2D and glucose traits. We sought to determine whether these loci were associated with transcript levels in adipose, muscle, liver, lymphocytes, and pancreatic β-cells. We found an excess of trans, rather than cis, associations among these SNPs in comparison to what was expected in adipose and muscle. Among transcripts differentially expressed (FDR < 0.05) between muscle or adipose cells of insulin-sensitive individuals and those of insulin-resistant individuals (matched on BMI), trans-regulated transcripts, in contrast to the cis-regulated ones, were enriched. The paucity of cis associations with transcripts was confirmed in a study of liver transcriptome and was further supported by an analysis of the most detailed transcriptome map of pancreatic β-cells. Relative to location- and allele-frequency-matched random SNPs, both the 68 loci and top T2D-associated SNPs from two large-scale genome-wide studies were enriched for trans eQTLs in adipose and muscle but not in lymphocytes. Our study suggests that T2D SNPs have broad-reaching and tissue-specific effects that often extend beyond local transcripts and raises the question of whether patterns of cis or trans transcript regulation are a key feature of the architecture of complex traits.

Integrating genetic association, genetics of gene expression, and single nucleotide polymorphism set analysis to identify susceptibility Loci for type 2 diabetes mellitus

Large-scale genome-wide association studies (GWAS) have identified over 40 genomic regions significantly associated with type 2 diabetes mellitus. However, GWAS results are not always straightforward to interpret, and linking these loci to meaningful disease etiology is often difficult without extensive follow-up studies. The authors expanded on previously reported type 2 diabetes mellitus GWAS from the nested case-control studies of 2 prospective US cohorts by incorporating expression single nucleotide polymorphism (SNP) information and applying SNP set enrichment analysis to identify sets of SNPs associated with genes that could provide further biologic insight to traditional genome-wide analysis. Using data collected between 1989 and 1994 in these previous studies to form a nested case-control study, the authors found that 3 of the most significantly associated SNPs to type 2 diabetes mellitus in their study are expression SNPs to the lymphocyte antigen 75 gene (LY75), the ubiquitin-specific peptidase 36 gene (USP36), and the phosphatidylinositol transfer protein, cytoplasmic 1 gene (PITPNC1). SNP set enrichment analysis of the GWAS results identified enrichment for expression SNPs to the macrophage-enriched module and the Gene Ontology (GO) biologic process fat cell differentiation human, which includes the transcription factor 7-like 2 gene (TCF7L2), as well as other type 2 diabetes mellitus-associated genes. Integrating genome-wide association, gene expression, and gene set analysis may provide valuable biologic support for potential type 2 diabetes mellitus susceptibility loci and may be useful in identifying new targets or pathways of interest for the treatment and prevention of type 2 diabetes mellitus.

AHI-1: a novel signaling protein and potential therapeutic target in human leukemia and brain disorders

Progress in the understanding of the molecular and cellular mechanisms of human cancer, including human leukemia and lymphomas, has been spurred by cloning of fusion genes created by chromosomal translocations or by retroviral insertional mutagenesis; a number of oncogenes and tumor suppressors involved in development of a number of malignancies have been identified in this manner. The BCR-ABL fusion gene, originating in a multipotent hematopoietic stem cell, is the molecular signature of chronic myeloid leukemia (CML). Discovery of this fusion gene has led to the development of one of the first successful targeted molecular therapies for cancer (Imatinib). It illustrates the advances that can result from an understanding of the molecular basis of disease. However, there still remain many as yet unidentified mutations that may influence the initiation or progression of human diseases. Thus, identification and characterization of the mechanism of action of genes that contribute to human diseases is an important and opportune area of current research. One promising candidate as a potential therapeutic target is Abelson helper integration site-1(Ahi-1/AHI-1) that was identified by retroviral insertional mutagenesis in murine models of leukemia/lymphomas and is highly elevated in certain human lymphoma and leukemia stem/progenitor cells. It encodes a unique protein with a SH3 domain, multiple SH3 binding sites and a WD40-repeat domain, suggesting that the normal protein has novel signaling activities. A new AHI-1-BCR-ABL-JAK2 interaction complex has recently been identified and this complex regulates transforming activities and drug resistance in CML stem/progenitor cells. Importantly, AHI-1 has recently been identified as a susceptibility gene involved in a number of brain disorders, including Joubert syndrome. Therefore, understanding molecular functions of the AHI-1 gene could lead to important and novel insights into disease processes involved in specific types of diseases. Ultimately, this knowledge will set the stage for translation into new and more effective diagnostic and treatment strategies.

Expression changes of hypothalamic Ahi1 in mice brain: implication in sensing insulin signaling

Growing evidence suggests that the brain, in particular the hypothalamus, directly senses hormones and nutrients to initiate feeding behavior and metabolic responses in the control of energy homeostasis. However, the molecular mechanisms underlying this important process have remained largely unknown. Our study provides the evidence for the role of Abelson helper integration site 1 (Ahi1) protein as a sensor of insulin signaling in the hypothalamus. We found that fasting increased the expression of hypothalamic Ahi1 which was accompanied by lower levels of circulating insulin compared with satiated mice, while re-feeding decreased the expression of hypothalamic Ahi1 which was accompanied by higher levels of circulating insulin. We also found the up-regulated expression of hypothalamic Ahi1 in high-fat induced obese mice, db/db mice, and streptozotocin induced diabetic mice. In addition, we demonstrated that insulin could decrease the expression of Ahi1 in neuroblastoma cell line N18TG2. Taken together, our results indicate that hypothalamic Ahi1 functions as a sensor of insulin signaling.

Ancestral susceptibility to colorectal cancer

Every year, approximately 1 million new colorectal cancer (CRC) cases are diagnosed and about half a million people worldwide die due to this cancer. Known differences in CRC incidence rates are mainly attributed to differences in diet and other environmental factors represented, among others, by nutrition-related complex diseases (e.g. obesity and diabetes mellitus type II). Within the last years, it has become evident that environmental risk factors can be complemented by a genetic component when considering the risk of CRC. For example, a number of polymorphisms are known to be associated with an increased risk of obesity and obesity is a risk factor for CRC. Several studies have shown that the 'ancestral-susceptibility model' can be reasonably applied to nutrition-related complex diseases such as obesity. The work in hand shortly discusses whether the ancestral-susceptibility model can also be applied to CRC as a nutrition-related complex disease.

Methods for meta-analyses of genome-wide association studies: critical assessment of empirical evidence

There has been a steep increase in the number of meta-analyses of genome-wide association (GWA) studies aimed at identifying genetic variants with increasingly smaller effects, but pressure to publish findings of new genetic associations has limited the time available for careful consideration of all of their methodological aspects. The authors surveyed the literature (2007-2010) to provide empirical evidence on the methods used in GWA meta-analyses, including their organization, requirements about the uniformity of methods used in primary studies, methods for data pooling, investigation of between-study heterogeneity, and quality of reporting. This review showed that a great variety of methods are being used, but the rationale for their choice is often unclear. It also highlights how important methodological aspects have received insufficient attention, potentially leading to missed opportunities for improving gene discovery and characterization. Evaluation of power to replicate findings was inadequate, and the number of variants selected for replication was not associated with replication sample size. A low proportion of GWA meta-analyses investigated the presence and magnitude of heterogeneity, even when there was little uniformity in methods used in primary studies. More methodological work is required before clear guidance can be offered as to optimal methods or tradeoffs between alternative methods. However, there is a clear need for guidelines for reporting the results of GWA meta-analyses.

Association of copy number variation in the AHI1 gene with risk of obesity in the Chinese population

OBJECTIVE

The prevalence of obesity has increased dramatically over the past decade. Gene copy number variants (CNVs) have been recognized as a hereditable source of susceptibility in human complex diseases including obesity. Recent studies have shown that Abelson helper integration site 1 (Ahi1) gene has a significant contribution in the homeostasis regulation in mouse models of obesity. A study was therefore carried out to investigate whether CNVs in AHI1 gene contribute to human obesity.

SUBJECTS AND METHODS

We analyzed samples from 70 Chinese overweight adults and 74 healthy controls for DNA copy number change using the Affymetrix single-nucleotide polymorphism (SNP) 6.0 array. Validation of CNVs of AHI1 was achieved by real-time PCR using the ΔΔC(t) method.

RESULTS

Copy number gain analysis revealed significant gains (P=0.0017) of AHI1 gene copy number in 17 of 70 (24.3%) samples but only four of 74 (5.4%) controls overall. Then we studied the frequency distribution of CNVs in AHI1 gene according to body mass index (BMI) grade. Five out of 28 (18.5%) at-risk obese, six out of 26 (26.9%) moderate obese, and six out of 17 (29.4%) severe obese subjects studied showed increased AHI1 gene copy number.

CONCLUSIONS

The result suggested that there was a significant linear trend for increasing AHI1 gene copy number frequencies with increasing BMI.

Population-specific association between a polymorphic variant in ST18, encoding a pro-apoptotic molecule, and pemphigus vulgaris

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by anti-epithelial antibodies, leading to disruption of cell-cell adhesion. Although the disease is exceedingly rare worldwide, it is known to be relatively prevalent in Jewish populations. The low prevalence of the disease represents a significant obstacle to a genome-wide approach to the mapping of susceptibility genes. We reasoned that the study of a genetically homogeneous cohort characterized by a high prevalence of PV may help exposing associated signals while reducing spurious results due to population sub-structure. We performed a genome-wide association study using 300K single-nucleotide polymorphisms (SNPs) in a case-control study of 100 PV patients of Jewish descent and 397 matched control individuals, followed by replication of significantly associated SNPs in three additional cohorts of Jewish, Egyptian, and German origin. In addition to the major histocompatibility complex locus, a genomic segment on 8q11.23 that spans the ST18 gene was also found to be significantly associated with PV. This association was confirmed in the Jewish and Egyptian replication sets but not in the German sample, suggesting that ST18-associated variants may predispose to PV in a population-specific manner. ST18 regulates apoptosis and inflammation, two processes of direct relevance to the pathogenesis of PV. Further supporting the relevance of ST18 to PV, we found this gene to be overexpressed in the skin of PV patients as compared with healthy individuals.

Genomic methods for clinical and translational pain research

Pain is a complex sensory experience for which the molecular mechanisms are yet to be fully elucidated. Individual differences in pain sensitivity are mediated by a complex network of multiple gene polymorphisms, physiological and psychological processes, and environmental factors. Here, we present the methods for applying unbiased molecular-genetic approaches, genome-wide association study (GWAS), and global gene expression analysis, to help better understand the molecular basis of pain sensitivity in humans and variable responses to analgesic drugs.

Twin studies in autoimmune disease: genetics, gender and environment

Twin studies are powerful tools to discriminate whether a complex disease is due to genetic or environmental factors. High concordance rates among monozygotic (MZ) twins support genetic factors being predominantly involved, whilst low rates are suggestive of environmental factors. Twin studies have often been utilised in the study of systemic and organ specific autoimmune diseases. As an example, type I diabetes mellitus has been investigated to establish that that disease is largely affected by genetic factors, compared to rheumatoid arthritis or scleroderma, which have a weaker genetic association. However, large twin studies are scarce or virtually non-existent in other autoimmune diseases which have been limited to few sets of twins and individual case reports. In addition to the study of the genetic and environmental contributions to disease, it is likely that twin studies will also provide data in regards to the clinical course of disease, as well as risk for development in related individuals. More importantly, genome-wide association studies have thus far reported genomic variants that only account for a minority of autoimmunity cases, and cannot explain disease discordance in MZ twins. Future research is therefore encouraged not only in the analysis of twins with autoimmune disease, but also in regards to epigenetic factors or rare variants that may be discovered with next-generation sequencing. This review will examine the literature surrounding twin studies in autoimmune disease including discussions of genetics and gender.

Emerging applications of metabolomic and genomic profiling in diabetic clinical medicine

Clinical and epidemiological metabolomics provides a unique opportunity to look at genotype-phenotype relationships as well as the body\x{2019}s responses to environmental and lifestyle factors. Fundamentally, it provides information on the universal outcome of influencing factors on disease states and has great potential in the early diagnosis, therapy monitoring, and understanding of the pathogenesis of disease. Diseases, such as diabetes, with a complex set of interactions between genetic and environmental factors, produce changes in the body\x{2019}s biochemical profile, thereby providing potential markers for diagnosis and initiation of therapies. There is clearly a need to discover new ways to aid diagnosis and assessment of glycemic status to help reduce diabetes complications and improve the quality of life. Many factors, including peptides, proteins, metabolites, nucleic acids, and polymorphisms, have been proposed as putative biomarkers for diabetes. Metabolomics is an approach used to identify and assess metabolic characteristics, changes, and phenotypes in response to influencing factors, such as environment, diet, lifestyle, and pathophysiological states. The specificity and sensitivity using metabolomics to identify biomarkers of disease have become increasingly feasible because of advances in analytical and information technologies. Likewise, the emergence of high-throughput genotyping technologies and genome-wide association studies has prompted the search for genetic markers of diabetes predisposition or susceptibility. In this review, we consider the application of key metabolomic and genomic methodologies in diabetes and summarize the established, new, and emerging metabolomic and genomic biomarkers for the disease. We conclude by summarizing future insights into the search for improved biomarkers for diabetes research and human diagnostics.