A genome-wide association study in American Indians implicates DNER as a susceptibility locus for type 2 diabetes

Neuroimaging Genomics a Predictor of Major Depressive Disorder (MDD)

Depression is a complex psychiatric disorder influenced by various genetic and environmental factors. Strong evidence has established the contribution of genetic factors in depression through twin studies and the heritability rate for depression has been reported to be 37%. Genetic studies have identified genetic variations associated with an increased risk of developing depression. Imaging genetics is an integrated approach where imaging measures are combined with genetic information to explore how specific genetic variants contribute to brain abnormalities. Neuroimaging studies allow us to examine both structural and functional abnormalities in individuals with depression. This review has been designed to study the correlation of the significant genetic variants with different regions of neural activity, connectivity, and structural alteration in the brain as detected by imaging techniques to understand the scope of biomarkers in depression. This might help in developing novel therapeutic interventions targeting specific genetic pathways or brain circuits and the underlying pathophysiology of depression based on this integrated approach can be established at length.

Tyrosine-phosphorylated DNER sensitizes insulin signaling in hepatic gluconeogenesis by inducing proteasomal degradation of TRB3

OBJECTIVE

Hepatic insulin resistance, which leads to increased hepatic gluconeogenesis, is a major contributor to fasting hyperglycemia in type 2 diabetes mellitus (T2DM). However, the mechanism of impaired insulin-dependent suppression of hepatic gluconeogenesis remains elusive. Delta/Notch-like epidermal growth factor (EGF)-related receptor (DNER), firstly described as a neuron-specific Notch ligand, has been recently identified as a susceptibility gene for T2DM through genome-wide association studies. We herein investigated whether DNER regulates hepatic gluconeogenesis and whether this is mediated by enhanced insulin signaling.

METHODS

The association between DNER, tribbles homolog 3 (TRB3) and Akt signaling was evaluated in C57BL/6J, ob/ob and db/db mice by western blot analysis. DNER loss-of-function and gain-of-function in hepatic gluconeogenesis were analyzed by western blot analysis, quantitative real-time PCR, glucose uptake and output assay in AML-12 cells and partially validated in primary mouse hepatocytes. Hepatic DNER knockdown mice were generated by tail vein injection of adenovirus to confirm the effects of DNER in vivo. The interaction between DNER and TRB3 was investigated by rescue experiments, cycloheximide chase analysis, co-immunoprecipitation and immunofluorescence. The potential insulin-stimulated phosphorylation sites of DNER were determined by co-immunoprecipitation, LC-MS/MS analysis and site-specific mutagenesis.

RESULTS

Here we show that DNER enhanced hepatic insulin signaling in gluconeogenesis by inhibiting TRB3, an endogenous Akt inhibitor, through the ubiquitin-proteasome degradation pathway. In AML-12 hepatocytes, insulin-stimulated activation of Akt and suppression of gluconeogenesis are attenuated by DNER knockdown, but potentiated by DNER over-expression. In C57BL/6J mice, hepatic DNER knockdown is accompanied by impaired glucose and pyruvate tolerance. Furthermore, the in vitro effects of DNER knockdown or over-expression on both Akt activity and hepatic gluconeogenesis can be rescued by TRB3 knockdown or over-expression, respectively. In response to insulin stimulation, DNER interacted directly with insulin receptor and was phosphorylated at Tyr677. This site-specific phosphorylation is essential for DNER to upregulate Akt activity and then downregulate G6Pase and PEPCK expression, by interacting with TRB3 directly and inducing TRB3 proteasome-dependent degradation.

CONCLUSIONS

Taken together, the crosstalk between insulin-Akt and DNER-TRB3 pathways represents a previously unrecognized mechanism by which insulin regulates hepatic gluconeogenesis.

Role of Delta/Notch-like EGF-related receptor in blood glucose homeostasis

Cell-cell interactions are necessary for optimal endocrine functions in the pancreas. β-cells, characterized by the expression and secretion of the hormone insulin, are a major constituent of functional micro-organs in the pancreas known as islets of Langerhans. Cell-cell contacts between β-cells are required to regulate insulin production and glucose-stimulated insulin secretion, which are key determinants of blood glucose homeostasis. Contact-dependent interactions between β-cells are mediated by gap junctions and cell adhesion molecules such as E-cadherin and N-CAM. Recent genome-wide studies have implicated Delta/Notch-like EGF-related receptor (Dner) as a potential susceptibility locus for Type 2 Diabetes in humans. DNER is a transmembrane protein and a proposed Notch ligand. DNER has been implicated in neuron-glia development and cell-cell interactions. Studies herein demonstrate that DNER is expressed in β-cells with an onset during early postnatal life and sustained throughout adulthood in mice. DNER loss in adult β-cells in mice (β-Dner cKO mice) disrupted islet architecture and decreased the expression of N-CAM and E-cadherin. β-Dner cKO mice also exhibited impaired glucose tolerance, defects in glucose- and KCl-induced insulin secretion, and decreased insulin sensitivity. Together, these studies suggest that DNER plays a crucial role in mediating islet cell-cell interactions and glucose homeostasis.

DNER and GNL2 are differentially m6A methylated in periodontitis in comparison with periodontal health revealed by m6A microarray of human gingival tissue and transcriptomic analysis

OBJECTIVE

This study aims to investigate the differences in the epigenomic patterns of N6-methyladenosine (m6A) methylation in gingival tissues between patients with periodontitis (PD) and healthy controls, identifying potential biomarkers.

BACKGROUND

As a multifactorial disease, PD involves multiple genetic and environmental effects. The m6A modification is the most prevalent internal mRNA modification and linked to various inflammatory diseases. However, the m6A modification pattern and m6A-related signatures in PD remain unclear.

MATERIALS AND METHODS

An m6A microarray of human gingival tissues was conducted in eight subjects: four diagnosed with PD and four healthy controls. Microarray analysis was performed to identify the differentially m6A methylated mRNAs (DMGs) and the differentially expressed mRNAs (DEGs). The differentially methylated and expressed mRNAs (DMEGs) were subjected to functional enrichment analysis by Metascape. The weighted gene co-expression network analysis (WGCNA) algorithm, the least absolute shrinkage and selection operator (LASSO) regression, and univariate logistic regression were performed to identify potential biomarkers. The cell type localization of the target genes was determined using single-cell RNA-seq (scRNA-seq) analysis. The m6A methylation level and gene expression of hub genes were subsequently verified by m6A methylated RNA immunoprecipitation (MeRIP) and quantitative real-time PCR (qRT-PCR).

RESULTS

In total, 458 DMGs, 750 DEGs, and 279 DMEGs were identified based on our microarray. Pathway analyses conducted for the DMEGs revealed that biological functions were mainly involved in the regulation of stem cell differentiation, ossification, circadian rhythm, and insulin secretion pathways. Besides, the genes involved in crucial biological processes were mainly expressed in fibroblast and epithelial cells. Furthermore, the m6A methylation and expression levels of two hub biomarkers (DNER and GNL2) were validated.

CONCLUSION

The current study exhibited a distinct m6A epitranscriptome, identified and verified two PD-related biomarkers (DNER and GNL2), which may provide novel insights into revealing the new molecular mechanisms and latent targets of PD.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

A conserved YAP/Notch/REST network controls the neuroendocrine cell fate in the lungs

The Notch pathway is a conserved cell-cell communication pathway that controls cell fate decisions. Here we sought to determine how Notch pathway activation inhibits the neuroendocrine cell fate in the lungs, an archetypal process for cell fate decisions orchestrated by Notch signaling that has remained poorly understood at the molecular level. Using intratumoral heterogeneity in small-cell lung cancer as a tractable model system, we uncovered a role for the transcriptional regulators REST and YAP as promoters of the neuroendocrine to non-neuroendocrine transition. We further identified the specific neuroendocrine gene programs repressed by REST downstream of Notch in this process. Importantly, we validated the importance of REST and YAP in neuroendocrine to non-neuroendocrine cell fate switches in both developmental and tissue repair processes in the lungs. Altogether, these experiments identify conserved roles for REST and YAP in Notch-driven inhibition of the neuroendocrine cell fate in embryonic lungs, adult lungs, and lung cancer.

Generation of Isogenic hiPSCs with Targeted Edits at Multiple Intronic SNPs to Study the Effects of the Type 2 Diabetes Associated KCNQ1 Locus in American Indians

The top genetic association signal for type 2 diabetes (T2D) in Southwestern American Indians maps to intron 15 of KCNQ1, an imprinted gene. We aim to understand the biology whereby variation at this locus affects T2D specifically in this genomic background. To do so, we obtained human induced pluripotent stem cells (hiPSC) derived from American Indians. Using these iPSCs, we show that imprinting of KCNQ1 and CDKN1C during pancreatic islet-like cell generation from iPSCs is consistent with known imprinting patterns in fetal pancreas and adult islets and therefore is an ideal model system to study this locus. In this report, we detail the use of allele-specific guide RNAs and CRISPR to generate isogenic hiPSCs that differ only at multiple T2D associated intronic SNPs at this locus which can be used to elucidate their functional effects. Characterization of these isogenic hiPSCs identified a few aberrant cell lines; namely cell lines with large hemizygous deletions in the putative functional region of KCNQ1 and cell lines hypomethylated at the KCNQ1OT1 promoter. Comparison of an isogenic cell line with a hemizygous deletion to the parental cell line identified CDKN1C and H19 as differentially expressed during the endocrine progenitor stage of pancreatic-islet development.

Limited extent and consequences of pancreatic SARS-CoV-2 infection

Concerns that infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), may cause new-onset diabetes persist in an evolving research landscape, and precise risk assessment is hampered by, at times, conflicting evidence. Here, leveraging comprehensive single-cell analyses of in vitro SARS-CoV-2-infected human pancreatic islets, we demonstrate that productive infection is strictly dependent on the SARS-CoV-2 entry receptor ACE2 and targets practically all pancreatic cell types. Importantly, the infection remains highly circumscribed and largely non-cytopathic and, despite a high viral burden in infected subsets, promotes only modest cellular perturbations and inflammatory responses. Similar experimental outcomes are also observed after islet infection with endemic coronaviruses. Thus, the limits of pancreatic SARS-CoV-2 infection, even under in vitro conditions of enhanced virus exposure, challenge the proposition that in vivo targeting of β cells by SARS-CoV-2 precipitates new-onset diabetes. Whether restricted pancreatic damage and immunological alterations accrued by COVID-19 increase cumulative diabetes risk, however, remains to be evaluated.

Celebrities in the heart, strangers in the pancreatic beta cell: Voltage-gated potassium channels Kv 7.1 and Kv 11.1 bridge long QT syndrome with hyperinsulinaemia as well as type 2 diabetes

Voltage‐gated potassium (K_v) channels play an important role in the repolarization of a variety of excitable tissues, including in the cardiomyocyte and the pancreatic beta cell. Recently, individuals carrying loss‐of‐function (LoF) mutations in KCNQ1, encoding K_v7.1, and KCNH2 (hERG), encoding K_v11.1, were found to exhibit post‐prandial hyperinsulinaemia and episodes of hypoglycaemia. These LoF mutations also cause the cardiac disorder long QT syndrome (LQTS), which can be aggravated by hypoglycaemia. Interestingly, patients with LQTS also have a higher burden of diabetes compared to the background population, an apparent paradox in relation to the hyperinsulinaemic phenotype, and KCNQ1 has been identified as a type 2 diabetes risk gene. This review article summarizes the involvement of delayed rectifier K⁺ channels in pancreatic beta cell function, with emphasis on K_v7.1 and K_v11.1, using the cardiomyocyte for context. The functional and clinical consequences of LoF mutations and polymorphisms in these channels on blood glucose homeostasis are explored using evidence from pre‐clinical, clinical and genome‐wide association studies, thereby evaluating the link between LQTS, hyperinsulinaemia and type 2 diabetes.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Effect of Rhizoma Drynariae on differential gene expression in ovariectomized rats with osteoporosis based on transcriptome sequencing

Osteoporosis is increasingly becoming a serious problem affecting the quality of life of the older population. Several experimental studies have shown that Chinese medicine has a definite effect on improving osteoporosis. Based on transcriptome sequencing, we analyzed the differential gene expression and mechanism of the related signaling pathways. Fifteen rats were randomly divided into an experimental group, a model group, and a sham surgery group. The rat model for menopausal osteoporosis was established using an ovariectomy method. One week after modeling, the experimental group was administered(intragastric administration)8.1 g/kg of Rhizoma drynariae, whereas the model and sham groups received 0.9% saline solution twice daily for 12 weeks. Subsequently, the rats were sacrificed, and the left femur of each group was removed for computerized tomography testing, while right femurs were used for hematoxylin and eosin staining. High-throughput RNA sequencing and functional and pathway enrichment analyses were performed. Comparing the gene expression between the experimental and model groups, 149 differential genes were identified, of which 44 were downregulated and 105 were upregulated. The criteria for statistical significance were |log2 Fold Change| > 1 and P < 0.05. Gene ontology analysis showed that the differentially expressed genes were enriched in cell component terms such as cell part and outer cell membrane part, and the genes were associated with cell process, biological regulation, metabolic processes, DNA transcription, and catalytic activity. Enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways showed significantly enriched pathways associated with systemic lupus erythematosus, herpes simplex infection, circadian rhythm, vascular smooth muscle contraction, the AGE-RAGE signaling pathway in diabetic complications, and the TNF, Apelin, and Ras signaling pathways. Our results revealed that the Npas2, Dbp, Rt1, Arntl, Grem2, H2bc9, LOC501233, Pla2g2c, Hpgd, Pde6c, and Dner genes, and the circadian rhythm, lipid metabolism, inflammatory signaling pathway, and immune pathways may be the key targets and pathways for traditional Chinese medicine therapy of Rhizoma Drynariae in osteoporosis.

Anticipation of Precision Diabetes and Promise of Integrative Multi-Omics

Precision diabetes is a concept of customizing delivery of health practices based on variability of diabetes. The authors reviewed recent research on type 2 diabetes heterogeneity and -omic biomarkers, including genomic, epigenomic, and metabolomic markers associated with type 2 diabetes. The emerging multiomics approach integrates complementary and interconnected molecular layers to provide systems level understanding of disease mechanisms and subtypes. Although the multiomic approach is not currently ready for routine clinical applications, future studies in the context of precision diabetes, particular in populations from diverse ethnic and demographic groups, may lead to improved diagnosis, treatment, and management of diabetes and diabetic complications.

Characterization of Exome Variants and Their Metabolic Impact in 6,716 American Indians from the Southwest US

Applying exome sequencing to populations with unique genetic architecture has the potential to reveal novel genes and variants associated with traits and diseases. We sequenced and analyzed the exomes of 6,716 individuals from a Southwestern American Indian (SWAI) population with well-characterized metabolic traits. We found that the SWAI population has distinct allelic architecture compared to populations of European and East Asian ancestry, and there were many predicted loss-of-function (pLOF) and nonsynonymous variants that were highly enriched or private in the SWAI population. We used pLOF and nonsynonymous variants in the SWAI population to evaluate gene-burden associations of candidate genes from European genome-wide association studies (GWASs) for type 2 diabetes, body mass index, and four major plasma lipids. We found 19 significant gene-burden associations for 11 genes, providing additional evidence for prioritizing candidate effector genes of GWAS signals. Interestingly, these associations were mainly driven by pLOF and nonsynonymous variants that are unique or highly enriched in the SWAI population. Particularly, we found four pLOF or nonsynonymous variants in APOB, APOE, PCSK9, and TM6SF2 that are private or enriched in the SWAI population and associated with low-density lipoprotein (LDL) cholesterol levels. Their large estimated effects on LDL cholesterol levels suggest strong impacts on protein function and potential clinical implications of these variants in cardiovascular health. In summary, our study illustrates the utility and potential of exome sequencing in genetically unique populations, such as the SWAI population, to prioritize candidate effector genes within GWAS loci and to find additional variants in known disease genes with potential clinical impact.

Identifying the association between single nucleotide polymorphisms in KCNQ1, ARAP1, and KCNJ11 and type 2 diabetes mellitus in a Chinese population

Background: Type 2 diabetes mellitus (T2DM) has a high global prevalence, and insufficient insulin secretion is one of the major reasons for its development. Therefore, investigating the association between T2DM and the single nucleotide polymorphisms (SNPs) in genes associated with insulin secretion is necessary. Methods: T2DM (1,194) and nondiabetic (NDM) (1,292) subjects were enrolled and the ten single nucleotide polymorphisms (SNPs) in KCNQ1, ARAP1, and KCNJ11 associated with insulin secretion were genotyped in a Chinese population. Results: Our data revealed that the rs2237897T allele in KCNQ1 is the protective allele for T2DM (P<0.001, OR=0.793; 95%CI: 0.705-0.893). However, the A allele of rs1552224 in ARAP1 may be a risk factor for T2DM (P=0.002, OR=12.070; 95% CI: 1.578-92.337). The haplotype analysis revealed that rs151290-rs2237892CC and rs2237895-rs2237897CC in KCNQ1 constitute the risk haplotype in T2DM development (P=0.010, OR=1.160; 95% CI: 1.037-1.299 and P=0.004, OR=1.192; 95% CI: 1.057-1.344). Moreover, rs2237895-rs2237897AT in KCNQ1 constitutes the protective haplotype in T2DM (P=0.001, OR=0.819; 95% CI: 0.727-0.923). In the inheritance models analysis, the rs2283228 (C/A-C/C) genotype is the protective factor compared to the A/A genotype (P=0.005, OR=0.79; 95% CI: 0.68-0.93). For rs2237897, the C/T-T/T genotype is the protective factor compared to the C/C genotype (P<0.001, OR=0.74; 95% CI: 0.63-0.87). Furthermore, when compared with the rs2237897 (C/T-T/T) genotype, rs2237897C/C genotype showed higher HbA1C levels (8.731±2.697 vs 9.282±2.921, P=0.001). Conclusion: Our results revealed that genetic variations in KCNQ1 and ARAP1 were associated with T2DM susceptibility in a Chinese population.

The Burmese cat as a genetic model of type 2 diabetes in humans

The recent extension of genetic tools to the domestic cat, together with the serendipitous consequences of selective breeding, have been essential to the study of the genetic diseases that affect them. Cats are increasingly presented for veterinary surveillance and share many of human's heritable diseases, allowing them to serve as natural models of these conditions. Feline diabetes mellitus is a common condition in domestic cats that bears close pathological and clinical resemblance to type 2 diabetes in humans, including pancreatic β-cell dysfunction and peripheral insulin resistance. In Australia, New Zealand and Europe, diabetes mellitus is almost four times more common in cats of the Burmese breed than in other breeds. This geographically based breed predisposition parallels familial and population clustering of type 2 diabetes in humans. As a genetically isolated population, the Australian Burmese breed provides a spontaneous, naturally occurring genetic model of type 2 diabetes. Genetically isolated populations typically exhibit extended linkage disequilibrium and increased opportunity for deleterious variants to reach high frequencies over many generations due to genetic drift. Studying complex diseases in such populations allows for tighter control of confounding factors including environmental heterogeneity, allelic frequencies and population stratification. The homogeneous genetic background of Australian Burmese cats may provide a unique opportunity to either refine genetic signals previously associated with type 2 diabetes or identify new risk factors for this disease.

Diabetes and cancer risk: A Mendelian randomization study

Earlier cohort studies using conventional regression models have consistently shown an increased cancer risk among individuals with type 2 diabetes. However, reverse causality and residual confounding due to common risk factors could exist, and it remains unclear whether diabetes per se contributes to cancer development. Mendelian randomization analyses might clarify the true association between diabetes and cancer risk. We conducted a case-cohort study with 10,536 subcohort subjects and 3,541 newly diagnosed cancer cases derived from 32,949 eligible participants aged 40-69 years within the Japan Public Health Center-based Prospective Study. With 29 known type 2 diabetes susceptibility variants, we used an inverse variance-weighted method to estimate hazard ratios for the associations of diabetes with risks of total and site-specific cancers. The hazard ratios of cancer per doubling of the probability of diabetes were 1.03 (95% confidence interval [CI], 0.92-1.15) overall, 1.08 (95% CI: 0.73-1.59) for the pancreas, 0.80 (95% CI: 0.57-1.14) for the liver and 0.90 (95% CI: 0.74-1.10) for the colorectum. Additional analyses, using publicly available large-scale genome-wide association study data on colorectal cancer in Japan, resulted in a narrower CI (hazard ratio: 1.00; 95% CI: 0.93-1.07). In this prospective Mendelian randomization study with a large number of incident cancer cases, we found no strong evidence to support associations between diabetes and overall and site-specific cancer risks. Our findings suggest that there is little evidence to support the genetic role of type 2 diabetes in cancer development in the Japanese population.

A Systemic Inflammatory Signature Reflecting Cross Talk Between Innate and Adaptive Immunity Is Associated With Incident Polyneuropathy: KORA F4/FF4 Study

Prospective analyses of biomarkers of inflammation and distal sensorimotor polyneuropathy (DSPN) are scarce and limited to innate immunity. We therefore aimed to assess associations between biomarkers reflecting multiple aspects of immune activation and DSPN. The study was based on 127 case subjects with incident DSPN and 386 noncase subjects from the population-based Cooperative Health Research in the Region of Augsburg (KORA) F4/FF4 cohort (follow-up 6.5 years). Proximity extension assay technology was used to measure serum levels of biomarkers of inflammation. Of 71 biomarkers assessed, 26 were associated with incident DSPN. After adjustment for multiple testing, higher levels of six biomarkers remained related to incident DSPN. Three of these proteins (MCP-3/CCL7, MIG/CXCL9, IP-10/CXCL10) were chemokines, and the other three (DNER, CD40, TNFRSF9) were soluble forms of transmembrane receptors. The chemokines had neurotoxic effects on neuroblastoma cells in vitro. Addition of all six biomarkers improved the C statistic of a clinical risk model from 0.748 to 0.783 (P = 0.011). Pathway analyses indicated that multiple cell types from innate and adaptive immunity are involved in the development of DSPN. We thus identified novel associations between biomarkers of inflammation and incident DSPN pointing to a complex cross talk between innate and adaptive immunity in the pathogenesis of the disease.

Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia

BACKGROUND

Intermediate hyperglycaemia (IH) is characterised by one or more measurements of elevated blood glucose concentrations, such as impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycosylated haemoglobin A1c (HbA1c). These levels are higher than normal but below the diagnostic threshold for type 2 diabetes mellitus (T2DM). The reduced threshold of 5.6 mmol/L (100 mg/dL) fasting plasma glucose (FPG) for defining IFG, introduced by the American Diabetes Association (ADA) in 2003, substantially increased the prevalence of IFG. Likewise, the lowering of the HbA1c threshold from 6.0% to 5.7% by the ADA in 2010 could potentially have significant medical, public health and socioeconomic impacts.

OBJECTIVES

To assess the overall prognosis of people with IH for developing T2DM, regression from IH to normoglycaemia and the difference in T2DM incidence in people with IH versus people with normoglycaemia.

SEARCH METHODS

We searched MEDLINE, Embase, ClincialTrials.gov and the International Clinical Trials Registry Platform (ICTRP) Search Portal up to December 2016 and updated the MEDLINE search in February 2018. We used several complementary search methods in addition to a Boolean search based on analytical text mining.

SELECTION CRITERIA

We included prospective cohort studies investigating the development of T2DM in people with IH. We used standard definitions of IH as described by the ADA or World Health Organization (WHO). We excluded intervention trials and studies on cohorts with additional comorbidities at baseline, studies with missing data on the transition from IH to T2DM, and studies where T2DM incidence was evaluated by documents or self-report only.

DATA COLLECTION AND ANALYSIS

One review author extracted study characteristics, and a second author checked the extracted data. We used a tailored version of the Quality In Prognosis Studies (QUIPS) tool for assessing risk of bias. We pooled incidence and incidence rate ratios (IRR) using a random-effects model to account for between-study heterogeneity. To meta-analyse incidence data, we used a method for pooling proportions. For hazard ratios (HR) and odds ratios (OR) of IH versus normoglycaemia, reported with 95% confidence intervals (CI), we obtained standard errors from these CIs and performed random-effects meta-analyses using the generic inverse-variance method. We used multivariable HRs and the model with the greatest number of covariates. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.

MAIN RESULTS

We included 103 prospective cohort studies. The studies mainly defined IH by IFG5.6 (FPG mmol/L 5.6 to 6.9 mmol/L or 100 mg/dL to 125 mg/dL), IFG6.1 (FPG 6.1 mmol/L to 6.9 mmol/L or 110 mg/dL to 125 mg/dL), IGT (plasma glucose 7.8 mmol/L to 11.1 mmol/L or 140 mg/dL to 199 mg/dL two hours after a 75 g glucose load on the oral glucose tolerance test, combined IFG and IGT (IFG/IGT), and elevated HbA1c (HbA1c5.7: HbA1c 5.7% to 6.4% or 39 mmol/mol to 46 mmol/mol; HbA1c6.0: HbA1c 6.0% to 6.4% or 42 mmol/mol to 46 mmol/mol). The follow-up period ranged from 1 to 24 years. Ninety-three studies evaluated the overall prognosis of people with IH measured by cumulative T2DM incidence, and 52 studies evaluated glycaemic status as a prognostic factor for T2DM by comparing a cohort with IH to a cohort with normoglycaemia. Participants were of Australian, European or North American origin in 41 studies; Latin American in 7; Asian or Middle Eastern in 50; and Islanders or American Indians in 5. Six studies included children and/or adolescents.Cumulative incidence of T2DM associated with IFG5.6, IFG6.1, IGT and the combination of IFG/IGT increased with length of follow-up. Cumulative incidence was highest with IFG/IGT, followed by IGT, IFG6.1 and IFG5.6. Limited data showed a higher T2DM incidence associated with HbA1c6.0 compared to HbA1c5.7. We rated the evidence for overall prognosis as of moderate certainty because of imprecision (wide CIs in most studies). In the 47 studies reporting restitution of normoglycaemia, regression ranged from 33% to 59% within one to five years follow-up, and from 17% to 42% for 6 to 11 years of follow-up (moderate-certainty evidence).Studies evaluating the prognostic effect of IH versus normoglycaemia reported different effect measures (HRs, IRRs and ORs). Overall, the effect measures all indicated an elevated risk of T2DM at 1 to 24 years of follow-up. Taking into account the long-term follow-up of cohort studies, estimation of HRs for time-dependent events like T2DM incidence appeared most reliable. The pooled HR and the number of studies and participants for different IH definitions as compared to normoglycaemia were: IFG5.6: HR 4.32 (95% CI 2.61 to 7.12), 8 studies, 9017 participants; IFG6.1: HR 5.47 (95% CI 3.50 to 8.54), 9 studies, 2818 participants; IGT: HR 3.61 (95% CI 2.31 to 5.64), 5 studies, 4010 participants; IFG and IGT: HR 6.90 (95% CI 4.15 to 11.45), 5 studies, 1038 participants; HbA1c5.7: HR 5.55 (95% CI 2.77 to 11.12), 4 studies, 5223 participants; HbA1c6.0: HR 10.10 (95% CI 3.59 to 28.43), 6 studies, 4532 participants. In subgroup analyses, there was no clear pattern of differences between geographic regions. We downgraded the evidence for the prognostic effect of IH versus normoglycaemia to low-certainty evidence due to study limitations because many studies did not adequately adjust for confounders. Imprecision and inconsistency required further downgrading due to wide 95% CIs and wide 95% prediction intervals (sometimes ranging from negative to positive prognostic factor to outcome associations), respectively.This evidence is up to date as of 26 February 2018.

AUTHORS' CONCLUSIONS

Overall prognosis of people with IH worsened over time. T2DM cumulative incidence generally increased over the course of follow-up but varied with IH definition. Regression from IH to normoglycaemia decreased over time but was observed even after 11 years of follow-up. The risk of developing T2DM when comparing IH with normoglycaemia at baseline varied by IH definition. Taking into consideration the uncertainty of the available evidence, as well as the fluctuating stages of normoglycaemia, IH and T2DM, which may transition from one stage to another in both directions even after years of follow-up, practitioners should be careful about the potential implications of any active intervention for people 'diagnosed' with IH.

Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study

Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS).

Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P < 4.13 × 10⁻⁷). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10⁻⁹). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B.

Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort.

Oncogene Delta/Notch-Like EGF-Related Receptor Promotes Cell Proliferation, Invasion, and Migration in Hepatocellular Carcinoma and Predicts a Poor Prognosis

PURPOSE

To determine the expression and function of Delta/Notch-like EGF-related receptor (DNER) in hepatocellular carcinoma (HCC).

METHODS

The expression of DNER in 84 HCC tissue samples and matched adjacent noncancerous specimens, as well as HCC cells, were evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. Survival analysis was evaluated using Kaplan-Meier method. For experiments in vitro, cell viability was measured by Cell Counting Kit-8 Assay and Colony Formation Assay. Furthermore, cell invasion and migration assays were performed with Transwell Assay.

RESULTS

The results showed that DNER was overexpressed in the tissues and cell lines of HCC (all, p < 0.05), and the upregulated expression of DNER was significantly correlated with advanced pathologic stage (p = 0.013) and pathologic-M1 (p = 0.012) in HCC patients. Survival analysis revealed that patients with high DNER levels had worse overall survival (OS) than those with low DNER levels (p = 0.004). More importantly, DNER could be an independent predictor of prognosis for OS (HR = 2.582, 95% CI 1.239-5.380, p = 0.011). In vitro, knockdown of DNER significantly suppressed cell proliferation, colony formation, cell invasion, and cell migration in HepG2 cells. Moreover, inhibition of DNER inactivated PI3K/AKT signaling pathway by downregulating the expression of p-PI3K, p-AKT, and p-70s6k.

CONCLUSIONS

Taken together, DNER could promote proliferation, migration, and invasion of HCC cells by regulating the activation of PI3K/AKT pathway, and it might act as a potential prognostic biomarker for HCC.

High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes

Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.

Identity-by-Descent Mapping Identifies Major Locus for Serum Triglycerides in Amerindians Largely Explained by an APOC3 Founder Mutation

BACKGROUND

Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment the inherent genetic information that can be used for localization.

METHODS AND RESULTS

Through identity-by-descent mapping, using ≈400 000 single-nucleotide polymorphisms (SNPs), of serum lipid profiles, we identified a major linkage signal for triglycerides in 1007 Pima Indians (LOD=9.23; P=3.5×10^-11 on chromosome 11q). In subsequent fine-mapping and replication association studies in ≈7500 Amerindians, we determined that this signal reflects effects of a loss-of-function Ala43Thr substitution in APOC3 (rs147210663) and 3 established functional SNPs in APOA5. The association with rs147210663 was particularly strong; each copy of the Thr allele conferred 42% lower triglycerides (β=-0.92±0.059 SD unit; P=9.6×10^-55 in 4668 Pimas and 2793 Southwest Amerindians combined). The Thr allele is extremely rare in most global populations but has a frequency of 2.5% in Pimas. We further demonstrated that 3 APOA5 SNPs with established functional impact could explain the association with the most well-replicated SNP (rs964184) for triglycerides identified by genome-wide association studies. Collectively, these 4 SNPs account for 6.9% of variation in triglycerides in Pimas (and 4.1% in Southwest Amerindians), and their inclusion in the original linkage model reduced the linkage signal to virtually null.

CONCLUSIONS

APOC3/APOA5 constitutes a major locus for serum triglycerides in Amerindians, especially the Pimas, and these results provide an empirical example for the concept that population-based linkage analysis is a useful strategy to identify complex trait variants.

Analysis of type 2 diabetes and obesity genetic variants in Mexican Pima Indians: Marked allelic differentiation among Amerindians at HLA

Prevalence of diabetes and obesity in Mexican Pima Indians is low, while prevalence in US Pima Indians is high. Although lifestyle likely accounts for much of the difference, the role of genetic factors is not well explored. To examine this, we genotyped 359 single nucleotide polymorphisms, including established type 2 diabetes and obesity variants from genome-wide association studies (GWAS) and 96 random markers, in 342 Mexican Pimas. A multimarker risk score of obesity variants was associated with body mass index (BMI; β = 0.81 kg/m² per SD, P = 0.0066). The mean value of the score was lower in Mexican Pimas than in US Pimas (P = 4.3 × 10^-11 ), and differences in allele frequencies at established loci could account for approximately 7% of the population difference in BMI; however, the difference in risk scores was consistent with evolutionary neutrality given genetic distance. To identify loci potentially under recent natural selection, allele frequencies at 283 variants were compared between US and Mexican Pimas, accounting for genetic distance. The largest differences were seen at HLA markers (e.g., rs9271720, difference = 0.75, P = 8.7 × 10^-9 ); genetic distances at HLA were greater than at random markers (P = 1.6 × 10^-46 ). Analyses of GWAS data in 937 US Pimas also showed sharing of alleles identical by descent at HLA that exceeds its genomic expectation (P = 7.0 × 10^-10 ). These results suggest that, in addition to the widely recognized balancing selection at HLA, recent directional selection may also occur, resulting in marked allelic differentiation between closely related populations.

Admixture mapping in the Hispanic Community Health Study/Study of Latinos reveals regions of genetic associations with blood pressure traits

Admixture mapping can be used to detect genetic association regions in admixed populations, such as Hispanics/Latinos, by estimating associations between local ancestry allele counts and the trait of interest. We performed admixture mapping of the blood pressure traits systolic and diastolic blood pressure (SBP, DBP), mean arterial pressure (MAP), and pulse pressure (PP), in a dataset of 12,116 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hispanics/Latinos have three predominant ancestral populations (European, African, and Amerindian), for each of which we separately tested local ancestry intervals across the genome. We identified four regions that were significantly associated with a blood pressure trait at the genome-wide admixture mapping level. A 6p21.31 Amerindian ancestry association region has multiple known associations, but none explained the admixture mapping signal. We identified variants that completely explained this signal. One of these variants had p-values of 0.02 (MAP) and 0.04 (SBP) in replication testing in Pima Indians. A 11q13.4 Amerindian ancestry association region spans a variant that was previously reported (p-value = 0.001) in a targeted association study of Blood Pressure (BP) traits and variants in the vitamin D pathway. There was no replication evidence supporting an association in the identified 17q25.3 Amerindian ancestry association region. For a region on 6p12.3, associated with African ancestry, we did not identify any candidate variants driving the association. It may be driven by rare variants. Whole genome sequence data may be necessary to fine map these association signals, which may contribute to disparities in BP traits between diverse populations.

A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose-raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10-8) or suggestively genome wide (p < 2.3 × 10-6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Admixture Mapping Identifies an Amerindian Ancestry Locus Associated with Albuminuria in Hispanics in the United States

Increased urine albumin excretion is highly prevalent in Hispanics/Latinos. Previous studies have found an association between urine albumin excretion and Amerindian ancestry in Hispanic/Latino populations. Admixture between racial/ethnic groups creates long-range linkage disequilibrium between variants with different allelic frequencies in the founding populations and it can be used to localize genes. Hispanic/Latino genomes are an admixture of European, African, and Amerindian ancestries. We leveraged this admixture to identify associations between urine albumin excretion (urine albumin-to-creatinine ratio [UACR]) and genomic regions harboring variants with highly differentiated allele frequencies among the ancestral populations. Admixture mapping analysis of 12,212 Hispanic Community Health Study/Study of Latinos participants, using a linear mixed model, identified three novel genome-wide significant signals on chromosomes 2, 11, and 16. The admixture mapping signal identified on chromosome 2, spanning q11.2-14.1 and not previously reported for UACR, is driven by a difference between Amerindian ancestry and the other two ancestries (P<5.7 × 10-5). Within this locus, two common variants located at the proapoptotic BCL2L11 gene associated with UACR: rs116907128 (allele frequency =0.14; P=1.5 × 10-7) and rs586283 (C allele frequency =0.35; P=4.2 × 10-7). In a secondary analysis, rs116907128 accounted for most of the admixture mapping signal observed in the region. The rs116907128 variant is common among full-heritage Pima Indians (A allele frequency =0.54) but is monomorphic in the 1000 Genomes European and African populations. In a replication analysis using a sample of full-heritage Pima Indians, rs116907128 significantly associated with UACR (P=0.01; n=1568). Our findings provide evidence for the presence of Amerindian-specific variants influencing the variation of urine albumin excretion in Hispanics/Latinos.

Assessing variation across 8 established East Asian loci for type 2 diabetes mellitus in American Indians: Suggestive evidence for new sex-specific diabetes signals in GLIS3 and ZFAND3

BACKGROUND

Eight new loci for type 2 diabetes mellitus (T2DM) were identified in an East Asian genome-wide association study meta-analysis. We assess tag SNPs across these loci for associations with T2DM in American Indians.

METHODS

A total of 435 SNPs that tag (R²  ≥ .85) common variation across the 8 loci were analyzed for association with T2DM (n = 7710), early onset T2DM (n = 1060), body mass index (n = 6839), insulin sensitivity (n = 555), and insulin secretion (n = 298).

RESULTS

Tag SNPs within FITM2-R3HDML-HNF4A, GLIS3, KCNK16, and ZFAND3 associated with T2DM after accounting for locus-wide multiple testing. The T2DM association in FITM2-R3HDML-HNF4A (rs3212183; P = .0002; OR = 1.19 [1.09-1.30]) was independent from the East Asian lead SNP (rs6017317), which did not associate with T2DM in American Indians. The top signals in GLIS3 (rs7875253; P = .0004; OR = 1.23 [1.10-1.38]) and KCNK16 (rs1544050; P = .002; OR = 1.16 [1.06-1.27]) were attenuated after adjustment for the East Asian lead SNPs (rs7041847 in GLIS3; rs1535500 in KCNK16), both of which also associated with T2DM in American Indians (P = .02; OR = 1.11 [1.01-1.21]; P = .007; OR = 1.19 [1.05-1.36] respectively). The top SNP in ZFAND3 (rs9470794; P = .002; OR = 1.43 [1.14-1.80]) was the identical East Asian lead SNP. Additional SNPs in GLIS3 (rs180867004) and ZFAND3 (rs4714120 and rs9470701) had significant genotype × sex interactions (P ≤ .008). The GLIS3 SNP (rs180867004) associated with T2DM only in men (P = .00006, OR = 1.94 [1.40-2.68]). The ZFAND3 SNPs (rs4714120 and rs9470701) associated with T2DM only in women (P = .0002, OR = 1.35 [1.16-1.59]; P = .0003, OR = 1.37 [1.16-1.63] respectively).

CONCLUSIONS

Replication of lead T2DM SNPs in GLIS3, KCNK16, and ZFAND3 was observed in American Indians. Sex-specific T2DM signals in GLIS3 and ZFAND3, which are distinct from the East Asian GWAS signals, were also identified.

Common and rare exonic MUC5B variants associated with type 2 diabetes in Han Chinese

Genome-wide association studies have identified over one hundred common genetic risk variants associated with type 2 diabetes (T2D). However, most of the heritability of T2D has not been accounted for. In this study, we investigated the contribution of rare and common variants to T2D susceptibility by analyzing exome array data in 1,908 Han Chinese genotyped with Affymetrix Axiom® Exome Genotyping Arrays. Based on the joint common and rare variants analysis of 57,704 autosomal SNPs within 12,244 genes using Sequence Kernel Association Tests (SKAT), we identified significant associations between T2D and 25 variants (9 rare and 16 common) in MUC5B, p-value 1.01×10⁻¹⁴. This finding was replicated (p = 0.0463) in an independent sample that included 10,401 unrelated individuals. Sixty-six of 1,553 possible haplotypes based on 25 SNPs within MUC5B showed significant association with T2D (Bonferroni corrected p values < 3.2×10⁻⁵). The expression level of MUC5B is significantly higher in pancreatic tissues of persons with T2D compared to those without T2D (p-value = 5×10⁻⁵). Our findings suggest that dysregulated MUC5B expression may be involved in the pathogenesis of T2D. As a strong candidate gene for T2D, MUC5B may play an important role in the mechanisms underlying T2D etiology and its complications.

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

Genetics of Type 2 Diabetes: the Power of Isolated Populations

Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.

The Arg59Trp variant in ANGPTL8 (betatrophin) is associated with total and HDL-cholesterol in American Indians and Mexican Americans and differentially affects cleavage of ANGPTL3

We previously identified a locus linked to total cholesterol (TC) concentration in Pima Indians on chromosome 19p. To characterize this locus, we genotyped >2000 SNPs in 1838 Pimas and assessed association with log(TC). We observed evidence for association with log(TC) with rs2278426 (3.5% decrease/copy of the T allele; P=5.045×10(-6)) in the ANGPTL8 (angiopoietin-like 8) gene. We replicated this association in 2413 participants of the San Antonio Mexican American Family Study (SAMAFS: 2.0% decrease per copy of the T allele; P=0.005842). In a meta-analysis of the combined data, we found the strongest estimated effect with rs2278426 (P=2.563×10(-7)). The variant T allele at rs2278426 predicts an Arg59Trp substitution and has previously been associated with LDL-C and HDL-C. In Pimas and SAMAFS participants, the T allele of rs2278426 was associated with reduced HDL-C levels (P=0.000741 and 0.00002, respectively), and the combined estimated effect for the two cohorts was -3.8% (P=8.526×10(-8)). ANGPTL8 transcript and protein levels increased in response to both glucose and insulin. The variant allele was associated with increased levels of cleaved ANGPTL3. We conclude that individuals with the variant allele may have lower TC and HDL-C levels due to increased activation of ANGPTL3 by ANGPTL8.

Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND)

Background

The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.

Results

A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.

Conclusions

The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.

Association between single nucleotide polymorphisms of delta/notch-like epidermal growth factor (EGF)-related receptor (DNER) and Delta-like 1 Ligand (DLL 1) with the risk of type 2 diabetes mellitus in a Chinese Han population

The aim of the study was to investigate the association between single nucleotide polymorphisms (SNPs), rs1861612 of delta/notch-like Epidermal Growth Factor (EGF)-related receptor (DNER) and rs1884190 in the Delta-like 1 ligand (DLL1) gene and type 2 diabetes mellitus (T2DM) susceptibility in a Chinese Han population. DNER rs1861612 and DLL1 rs1884190 polymorphisms were genotyped in patients with T2DM and age- and sex-matched T2DM-free controls from a Chinese Han population. A total of 298 patients with T2DM and 500 controls were enrolled in this study. We found that TC and TT genotypes of rs1861612 and variant T were associated with a significantly increased risk of T2DM. In contrast, the AG and AA genotypes of rs1884190 were not significantly associated with the risk of T2DM, even after further stratification analysis based on age or sex. Our results showed that DNER rs1861612 C to T change and variant T genotype may contribute to T2DM in a Chinese Han population.

Complex Genetics of Type 2 Diabetes and Effect Size: What have We Learned from Isolated Populations?

Genetic studies in large outbred populations have documented a complex, highly polygenic basis for type 2 diabetes (T2D). Most of the variants currently known to be associated with T2D risk have been identified in large studies that included tens of thousands of individuals who are representative of a single major ethnic group such as European, Asian, or African. However, most of these variants have only modest effects on the risk for T2D; identification of definitive 'causal variant' or 'causative loci' is typically lacking. Studies in isolated populations offer several advantages over outbred populations despite being, on average, much smaller in sample size. For example, reduced genetic variability, enrichment of rare variants, and a more uniform environment and lifestyle, which are hallmarks of isolated populations, can reduce the complexity of identifying disease-associated genes. To date, studies in isolated populations have provided valuable insight into the genetic basis of T2D by providing both a deeper understanding of previously identified T2D-associated variants (e.g. demonstrating that variants in KCNQ1 have a strong parent-of-origin effect) or providing novel variants (e.g. ABCC8 in Pima Indians, TBC1D4 in the Greenlandic population, HNF1A in Canadian Oji-Cree). This review summarizes advancements in genetic studies of T2D in outbred and isolated populations, and provides information on whether the difference in the prevalence of T2D in different populations (Pima Indians vs. non-Hispanic Whites and non-Hispanic Whites vs. non-Hispanic Blacks) can be explained by the difference in risk allele frequencies of established T2D variants.

ABCC8 R1420H Loss-of-Function Variant in a Southwest American Indian Community: Association With Increased Birth Weight and Doubled Risk of Type 2 Diabetes

Missense variants in KCNJ11 and ABCC8, which encode the KIR6.2 and SUR1 subunits of the β-cell KATP channel, have previously been implicated in type 2 diabetes, neonatal diabetes, and hyperinsulinemic hypoglycemia of infancy (HHI). To determine whether variation in these genes affects risk for type 2 diabetes or increased birth weight as a consequence of fetal hyperinsulinemia in Pima Indians, missense and common noncoding variants were analyzed in individuals living in the Gila River Indian Community. A R1420H variant in SUR1 (ABCC8) was identified in 3.3% of the population (N = 7,710). R1420H carriers had higher mean birth weights and a twofold increased risk for type 2 diabetes with a 7-year earlier onset age despite being leaner than noncarriers. One individual homozygous for R1420H was identified; retrospective review of his medical records was consistent with HHI and a diagnosis of diabetes at age 3.5 years. In vitro studies showed that the R1420H substitution decreases KATP channel activity. Identification of this loss-of-function variant in ABCC8 with a carrier frequency of 3.3% affects clinical care as homozygous inheritance and potential HHI will occur in 1/3,600 births in this American Indian population.

Comparative Genome of GK and Wistar Rats Reveals Genetic Basis of Type 2 Diabetes

The Goto-Kakizaki (GK) rat, which has been developed by repeated inbreeding of glucose-intolerant Wistar rats, is the most widely studied rat model for Type 2 diabetes (T2D). However, the detailed genetic background of T2D phenotype in GK rats is still largely unknown. We report a survey of T2D susceptible variations based on high-quality whole genome sequencing of GK and Wistar rats, which have generated a list of GK-specific variations (228 structural variations, 2660 CNV amplification and 2834 CNV deletion, 1796 protein affecting SNVs or indels) by comparative genome analysis and identified 192 potential T2D-associated genes. The genes with variants are further refined with prior knowledge and public resource including variant polymorphism of rat strains, protein-protein interactions and differential gene expression. Finally we have identified 15 genetic mutant genes which include seven known T2D related genes (Tnfrsf1b, Scg5, Fgb, Sell, Dpp4, Icam1, and Pkd2l1) and eight high-confidence new candidate genes (Ldlr, Ccl2, Erbb3, Akr1b1, Pik3c2a, Cd5, Eef2k, and Cpd). Our result reveals that the T2D phenotype may be caused by the accumulation of multiple variations in GK rat, and that the mutated genes may affect biological functions including adipocytokine signaling, glycerolipid metabolism, PPAR signaling, T cell receptor signaling and insulin signaling pathways. We present the genomic difference between two closely related rat strains (GK and Wistar) and narrow down the scope of susceptible loci. It also requires further experimental study to understand and validate the relationship between our candidate variants and T2D phenotype. Our findings highlight the importance of sequenced-based comparative genomics for investigating disease susceptibility loci in inbreeding animal models.

Association of type 2 diabetes GWAS loci and the risk of Parkinson's and Alzheimer's diseases

BACKGROUND

Insulin and insulin-like growth factor contribute to normal brain function. Recent experimental and clinical studies showed that type 2 diabetes mellitus (T2DM) and Parkinson's disease (PD) or Alzheimer's disease (AD) share several dysregulated pathways.

OBJECTIVE

We aimed to investigate whether genome-wide significant loci of T2DM are associated with the risk of PD and AD as well as the severity of cognitive impairment.

METHODS

Study subjects were 500 PD patients, 400 AD patients, and 500 unrelated controls. We selected 32 genetic variants from 11 genes (CDC123, CDKAL1, CDKN2B, FTO, GLIS3, HHEX, IGF2BP2, KCNJ11, KCNQ1, SLC30A8, and TCF7L2) and intergenic regions based on results of recent genome-wide association studies (GWAS) in T2DM. These variants were reported to be T2DM-susceptibility loci and have been replicated in other independent studies. All association analyses were performed using logistic regression models, adjusting for age and sex.

RESULTS

KCNQ1 SNP rs163182 showed the strongest association with AD, but it was not significant after Bonferroni correction (OR = 1.30, 95% CI = 1.07-1.59, Pcorrected = 0.32). In PD patients, CDC123 SNP rs11257655 showed modest association with MMSE score <26, and CDKN2B SNPs (rs2383208, rs10965250, and rs10811661) showed modest association with MoCA score <26, which were not significant after Bonferroni correction. Other genetic variants had no association with the risk of PD or AD and the severity of cognitive impairment.

CONCLUSIONS

Our results suggest that genome-wide significant loci of T2DM play no major role in the risk and cognitive impairment of PD and AD.

Assessing FOXO1A as a potential susceptibility locus for type 2 diabetes and obesity in American Indians

OBJECTIVE

A prior genome-wide association study (GWAS) in Pima Indians identified variation within FOXO1A that modestly associated with early-onset (onset age < 25 years) type 2 diabetes (T2D). FOXO1A encodes the forkhead transcription factor involved in pancreatic β-cell growth and hypothalamic energy balance; therefore, FOXO1A was analyzed as a candidate gene for T2D and obesity in a population-based sample of 7,710 American Indians.

METHODS

Tag SNPs in/near FOXO1A (minor allele frequency ≥ 0.05) were analyzed for association with T2D at early onset (n = 1,060) and all ages (n = 7,710) and with insulin secretion (n = 298). SNPs were also analyzed for association with maximum body mass index (BMI) in adulthood (n = 5,918), maximum BMI z-score in childhood (n = 5,350), and % body fat (n = 555).

RESULTS

An intronic SNP rs2297627 associated with early-onset T2D [OR = 1.34 (1.13-1.58), P = 8.7 × 10(-4)] and T2D onset at any age [OR = 1.19 (1.09-1.30), P = 1 × 10(-4) ]. The T2D risk allele also associated with lower acute insulin secretion (β = 0.88, as a multiplier, P = 0.02). Another intronic SNP (rs1334241, D' = 0.99, r(2) = 0.49 with rs2297627) associated with maximum adulthood BMI (β = 1.02, as a multiplier, P = 3 × 10(-5)), maximum childhood BMI z-score (β = 0.08, P = 3 × 10(-4)), and % body fat (β = 0.83%, P = 0.04).

CONCLUSIONS

Common variation in FOXO1A may modestly affect risk for T2D and obesity in American Indians.

Genetics, genomics and personalized medicine in Type 2 diabetes: a perspective on the Arab region

Type 2 diabetes (T2D) is a wide-spread, chronic metabolic disorder, affecting millions of people worldwide. The epidemic of diabetes has placed a huge strain on public health, longevity and economy. T2D occurs as a result of both genetic and environmental factors and is heterogeneous in its presentation across individuals. This review gives an overview of the genetic variations identified by genome-wide association studies which predispose individuals to T2D and those which are responsible for variable drug response across patients, and the necessity to adopt a personalized approach to diabetes management. We also include a perspective on diabetes in Arabs, given the high incidence of T2D and consanguineous marriages, and the need to understand associated genetic components in this vulnerable population.

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.

Role of Established Type 2 Diabetes-Susceptibility Genetic Variants in a High Prevalence American Indian Population

Several single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM) have been identified, but there is little information on their role in populations at high risk for T2DM. We genotyped SNPs at 63 T2DM loci in 3,421 individuals from a high-risk American Indian population. Nominally significant (P < 0.05) associations were observed at nine SNPs in a direction consistent with the established association. A genetic risk score derived from all loci was strongly associated with T2DM (odds ratio 1.05 per risk allele, P = 6.2 × 10(-6)) and, in 292 nondiabetic individuals, with lower insulin secretion (by 4% per copy, P = 4.1 × 10(-6)). Genetic distances between American Indians and HapMap populations at T2DM markers did not differ significantly from genomic expectations. Analysis of U.S. national survey data suggested that 66% of the difference in T2DM prevalence between African Americans and European Americans, but none of the difference between American Indians and European Americans, was attributable to allele frequency differences at these loci. These analyses suggest that, in general, established T2DM loci influence T2DM in American Indians and that risk is mediated in part through an effect on insulin secretion. However, differences in allele frequencies do not account for the high population prevalence of T2DM.

Diabetes and Kidney Disease in American Indians: Potential Role of Sugar-Sweetened Beverages

Since the early 20th century, a marked increase in obesity, diabetes, and chronic kidney disease has occurred in the American Indian population, especially the Pima Indians of the Southwest. Here, we review the current epidemic and attempt to identify remediable causes. A search was performed using PubMed and the search terms American Indian and obesity, American Indian and diabetes, American Indian and chronic kidney disease, and American Indian and sugar or fructose, Native American, Alaska Native, First Nations, Aboriginal, Amerind, and Amerindian for American Indian for articles linking American Indians with diabetes, obesity, chronic kidney disease, and sugar; additional references were identified in these publications traced to 1900 and articles were reviewed if they were directly discussing these topics. Multiple factors are involved in the increased risk for diabetes and kidney disease in the American Indian population, including poverty, overnutrition, poor health care, high intake of sugar, and genetic mechanisms. Genetic factors may be especially important in the Pima, as historical records suggest that this group was predisposed to obesity before exposure to Western culture and diet. Exposure to sugar-sweetened beverages may also be involved in the increased risk for chronic kidney disease. In these small populations in severe health crisis, we recommend further studies to investigate the role of excess added sugar, especially sugar-sweetened beverages, as a potentially remediable risk factor.

Fast eQTL Analysis for Twin Studies

Twin data are commonly used for studying complex psychiatric disorders, and mixed effects models are one of the most popular tools for modeling dependence structures between twin pairs. However, for eQTL (expression quantitative trait loci) data where associations between thousands of transcripts and millions of single nucleotide polymorphisms need to be tested, mixed effects models are computationally inefficient and often impractical. In this paper, we propose a fast eQTL analysis approach for twin eQTL data where we randomly split twin pairs into two groups, so that within each group the samples are unrelated, and we then apply a multiple linear regression analysis separately to each group. A score statistic that automatically adjusts the (hidden) correlation between the two groups is constructed for combining the results from the two groups. The proposed method has well-controlled type I error. Compared to mixed effects models, the proposed method has similar power but drastically improved computational efficiency. We demonstrate the computational advantage of the proposed method via extensive simulations. The proposed method is also applied to a large twin eQTL data from the Netherlands Twin Register.

Rare and common genetic events in type 2 diabetes: what should biologists know?

Type 2 diabetes (T2D) had long been referred to as the "geneticist's nightmare." Genome-wide association studies have fully confirmed the polygenic nature of T2D, demonstrating the role of many genes in T2D risk. The increasingly busier picture of T2D genetics is quite difficult to understand for the diabetes research community, which can create misunderstandings with geneticists, and can eventually limit both basic research and translational outcomes of these genetic discoveries. The present review wishes to lift the fog around genetics of T2D with the hope that it will foster integrated diabetes modeling approaches from genetic defects to personalized medicine.

A cis-eQTL in PFKFB2 is associated with diabetic nephropathy, adiposity and insulin secretion in American Indians

A prior genome-wide association study (GWAS) in Pima Indians identified a variant within PFKFB2 (rs17258746) associated with body mass index (BMI). PFKFB2 encodes 6-phosphofructo-2-kinase/fructose 2,6-bisphosphatase isoform 2, which plays a role in glucose metabolism. To follow-up on the GWAS, tag SNPs across PFKFB2 were genotyped in American Indians (AI) who had longitudinal data on BMI (n = 6839), type 2 diabetes (T2D; n = 7710), diabetic nephropathy (DN; n = 2452), % body fat (n = 555) and insulin secretion (n = 298). Two SNPs were further genotyped in urban AI to assess replication for DN (n = 864). PFKFB2 expression was measured in 201 adipose biopsies using real-time RT-PCR and 61 kidney biopsies using the Affymetrix U133 array. Two SNPs (rs17258746 and rs11120137), which capture the same signal, were associated with maximum BMI in adulthood (β = 1.02 per risk allele, P = 7.3 × 10(-4)), maximum BMI z-score in childhood (β = 0.079, P = 0.03) and % body fat in adulthood (β = 3.4%, P = 3 × 10(-7)). The adiposity-increasing allele correlated with lower PFKFB2 adipose expression (β = 0.81, P = 9.4 × 10(-4)). Lower expression of PFKFB2 further correlated with higher % body fat (r = -0.16, P = 0.02) and BMI (r = -0.17, P = 0.02). This allele was also associated with increased risk for DN in both cohorts of AI [odds ratio = 1.64 (1.32-2.02), P = 5.8 × 10(-6)], and similarly correlated with lower PFKFB2 expression in kidney glomeruli (β = 0.87, P = 0.03). The same allele was also associated with lower insulin secretion assessed by acute insulin response (β = 0.78, P = 0.03) and 30-min plasma insulin concentrations (β = 0.78, P = 1.1 × 10(-4)). Variation in PFKFB2 appears to reduce PFKFB2 expression in adipose and kidney tissues, and thereby increase risk for adiposity and DN.

Genetics of kidney disease and related cardiometabolic phenotypes in Zuni Indians: the Zuni Kidney Project

The objective of this study is to identify genetic factors associated with chronic kidney disease (CKD) and related cardiometabolic phenotypes among participants of the Genetics of Kidney Disease in Zuni Indians study. The study was conducted as a community-based participatory research project in the Zuni Indians, a small endogamous tribe in rural New Mexico. We recruited 998 members from 28 extended multigenerational families, ascertained through probands with CKD who had at least one sibling with CKD. We used the Illumina Infinium Human1M-Duo version 3.0 BeadChips to type 1.1 million single nucleotide polymorphisms (SNPs). Prevalence estimates for CKD, hyperuricemia, diabetes, and hypertension were 24%, 30%, 17% and 34%, respectively. We found a significant (p < 1.58 × 10^-7) association for a SNP in a novel gene for serum creatinine (PTPLAD2). We replicated significant associations for genes with serum uric acid (SLC2A9), triglyceride levels (APOA1, BUD13, ZNF259), and total cholesterol (PVRL2). We found novel suggestive associations (p < 1.58 × 10^-6) for SNPs in genes with systolic (OLFML2B), and diastolic blood pressure (NFIA). We identified a series of genes associated with CKD and related cardiometabolic phenotypes among Zuni Indians, a population with a high prevalence of kidney disease. Illuminating genetic variations that modulate the risk for these disorders may ultimately provide a basis for novel preventive strategies and therapeutic interventions.

Variants associated with type 2 diabetes identified by the transethnic meta-analysis study: assessment in American Indians and evidence for a new signal in LPP

AIM/HYPOTHESIS

A recent genome-wide trans-ancestry meta-analysis identified seven new loci associated with type 2 diabetes. We assessed the replication of the seven lead single nucleotide polymorphisms (SNPs) and evaluated these loci for additional signals in American Indians.

METHODS

Seven SNPs were genotyped in 7,710 individuals from a longitudinally studied American Indian population, and associations with type 2 diabetes, BMI and related phenotypes were assessed. Previous genome-wide association study (GWAS) data from these individuals were used to screen for additional type 2 diabetes signals at these loci. A variant independent of the trans-ancestry meta-analysis was identified within LPP, and its replication was assessed in an additional 3,106 urban American Indians.

RESULTS

SNP rs6813195 near to TMEM154 was nominally associated with type 2 diabetes (p = 0.01, OR 1.12 [95% CI 1.03, 1.22]) and adiposity: the type 2 diabetes risk allele was associated with a lower percentage body fat (β = -1.451%, p = 4.8 × 10(-4)). Another SNP, rs3130501 near to POU5F1-TCF19, was associated with BMI (β = -0.012, p = 0.004), type 2 diabetes adjusted for BMI (p = 0.02, OR 1.11 [95% CI 1.02, 1.22]), 2 h glucose concentrations (β = 0.080 mmol/l, p = 0.02) and insulin resistance estimated by homeostatic model (β = 0.039, p = 0.009). The independent variant identified at the LPP locus in our American Indian GWAS for type 2 diabetes was replicated in the additional samples (all American Indian meta-analysis, p = 8.9 × 10(-6), OR 1.29 [95% CI 1.15, 1.45]).

CONCLUSIONS/INTERPRETATION

For two of the seven newly identified variants, there was nominal evidence for association with type 2 diabetes and related traits in American Indians. Identification of an independent variant at the LPP locus suggests the existence of more than one type 2 diabetes signal at this locus.