A Federated Database for Obesity Research: An IMI-SOPHIA Study.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Disruptive mutations in the serotonin transporter associate serotonin dysfunction with treatment-resistant affective disorder.

Affective or mood disorders are a leading cause of disability worldwide. The serotonergic system has been heavily implicated in the complex etiology and serves as a therapeutic target. The serotonin transporter (SERT) is a major regulator of serotonin neurotransmission, yet the disease-relevance of impaired SERT function remains unknown. Here, we present the first identification and functional characterization of disruptive coding SERT variants found in patients with psychiatric diseases. In a unique cohort of 144 patients characterized by treatment-resistant chronic affective disorders with a lifetime history of electroconvulsive therapy, we identified two previously uncharacterized coding SERT variants: SERT-N217S and SERT-A500T. Both variants were significantly enriched in the patient cohort compared to GnomAD (SERT-N217S: OR = 151, P = 0.0001 and SERT-A500T: OR = 1348, P = 0.0022) and ethnicity-matched healthy controls (SERT-N217S: OR ≥ 17.7, P ≤ 0.013 and SERT-A500T: OR = ∞, P = 0.029). Functional investigations revealed that the mutations exert distinct perturbations to SERT function, but their overall effects converge on a partial loss-of-function molecular phenotype. Thus, the SERT-A500T variant compromises the catalytic activity, while SERT-N217S disrupts proper glycosylation of SERT with a resulting dominant-negative trafficking deficiency. Moreover, we demonstrate that the trafficking deficiency of SERT-N217S is amenable to pharmacochaperoning by noribogaine. Collectively, our findings describe the first disease-associated loss-of-function SERT variants and implicate serotonergic disturbances arising from SERT dysfunction as a risk factor for chronic affective disorders.

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus.

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

Transcriptomic analysis links diverse hypothalamic cell types to fibroblast growth factor 1-induced sustained diabetes remission.

In rodent models of type 2 diabetes (T2D), sustained remission of hyperglycemia can be induced by a single intracerebroventricular (icv) injection of fibroblast growth factor 1 (FGF1), and the mediobasal hypothalamus (MBH) was recently implicated as the brain area responsible for this effect. To better understand the cellular response to FGF1 in the MBH, we sequenced >79,000 single-cell transcriptomes from the hypothalamus of diabetic Lepob/ob mice obtained on Days 1 and 5 after icv injection of either FGF1 or vehicle. A wide range of transcriptional responses to FGF1 was observed across diverse hypothalamic cell types, with glial cell types responding much more robustly than neurons at both time points. Tanycytes and ependymal cells were the most FGF1-responsive cell type at Day 1, but astrocytes and oligodendrocyte lineage cells subsequently became more responsive. Based on histochemical and ultrastructural evidence of enhanced cell-cell interactions between astrocytes and Agrp neurons (key components of the melanocortin system), we performed a series of studies showing that intact melanocortin signaling is required for the sustained antidiabetic action of FGF1. These data collectively suggest that hypothalamic glial cells are leading targets for the effects of FGF1 and that sustained diabetes remission is dependent on intact melanocortin signaling.

Prevalence of rearrangements in the 22q11.2 region and population-based risk of neuropsychiatric and developmental disorders in a Danish population: a case-cohort study.

BACKGROUND: Although the pathogenic nature of copy number variants (CNVs) on chromosome 22q11.2 has been recognised for decades, unbiased estimates of their population prevalence, mortality, disease risks, and diagnostic trajectories are absent. We aimed to provide the true population prevalence of 22q11.2 CNVs and associated trajectory of disease risk and mortality by use of the unbiased, representative Danish iPSYCH population case cohort. METHODS: This case-cohort study was done on a population of 86 189 individuals selected from the iPSYCH case cohort of 1 472 762 singletons born in Denmark between May 1, 1981, and Dec 31, 2005, who have a known mother from the Danish Civil Registration System, were residents in Denmark at 1 year of age, and enrolled in the iPSYCH Initiative. We used epidemiological methods in conjunction with nationwide hospital registers to analyse the iPSYCH case cohort of individuals with attention-deficit hyperactivity disorder (ADHD), major depressive disorder, schizophrenia, autism, or bipolar disorder and a random population-based sample. The main outcomes assessed were the population prevalence of 22q11.2 rearrangements, and associated unbiased, population-adjusted estimates and 31-year disease risk trajectories for major neuropsychiatric disorders. FINDINGS: Population prevalence in the Danish population was one in 3672 (seven of 25 704 [0·027%; 95% CI 0·012-0·057]) for deletions and one in 1606 (17 of 25 704 [0·066%; 0·040-0·107]) for duplications. Mortality after the age of 1 year among carriers was zero, and hazard ratios for neuropsychiatric disorders ranged from 2·60 to 82·44 for both rearrangements. By the age of 32 years, about 10% of individuals with deletions or duplications had developed ADHD, autism, or intellectual disability, and deletion carriers had higher probability than duplication carriers of co-occurring intellectual disability or epilepsy. INTERPRETATION: The significantly different prevalence of 22q11.2 duplications and deletions indicates distinct selective pressures on these rearrangements. Although risk of congenital abnormalities, developmental delay, and intellectual disability is elevated in deletion carriers, the overall prevalence of neuropsychiatric disorders is higher in duplication carriers, which implies that identification and clinical monitoring should extend beyond congenital traits and into child and adolescent psychiatry. FUNDING: Capital Region's Research Foundation for Mental Health Research, The Lundbeck Foundation, and US National Institutes of Health.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m2). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m2 for each Mb of total deletion burden (P = 2.5 × 10-10, 6.0 × 10-5, and 2.9 × 10-3). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Risk of Psychiatric Disorders Among Individuals With the 22q11.2 Deletion or Duplication: A Danish Nationwide, Register-Based Study.

Importance: Microdeletions and duplications have been described at the 22q11.2 locus. However, little is known about the clinical and epidemiologic consequences at the population level. Objective: To identify indicators of deletions or duplications at the 22q11.2 locus and estimate the incidence rate ratios (IRRs) and absolute risk for psychiatric disorders in clinically identified individuals with 22q11.2 deletion or duplication. Design, Setting, and Participants: A Danish nationwide register study including all individuals recorded in the Danish Cytogenetic Central Register with a 22q11.2 deletion or duplication was performed. A total of 3 768 943 individuals born in Denmark from 1955 to 2012 were followed up during the study period (total follow-up, 57.1 million person-years). Indicators of 22q11.2 deletion or duplication and cumulative incidences were estimated using a nested case-control design that included individuals from the population-based cohort. Survival analysis was used to compare risk of disease in individuals with and without the 22q11.2 deletion or duplication. The study was conducted from May 7, 2015, to August 14, 2016. Exposure: The 22q11.2 deletion or duplication. Main Outcomes and Measures: Indicators for carrying a 22q11.2 deletion or duplication, IRR, and cumulative incidences for psychiatric diagnoses (International Statistical Classification of Diseases and Related Health Problems, 10th Revision, codes F00-F99), including schizophrenia-spectrum disorders, mood disorders, neurotic stress-related and somatoform disorders, and a range of developmental and childhood disorders. Results: Among the 3 768 943 participants, 244 (124 [50.8%] male) and 58 (29 [50.0%] male) individuals were clinically identified with a 22q11.2 deletion or duplication, respectively. Mean (SD) age at diagnosis of any psychiatric disorder was 12.5 (8.3) years for individuals with deletions and 6.1 (0.9) years for duplication carriers. A parental diagnosis of schizophrenia-but not of other psychiatric diagnoses-was associated with a 22q11.2 deletion, and parental psychiatric diagnoses other than schizophrenia were associated with duplication carrier status. Both the 22q11.2 deletion (IRR, 4.24; 95% CI, 3.07-5.67) and duplication (IRR, 4.99; 95% CI, 1.79-10.72) was associated with increased risk of any psychiatric disorders. Furthermore, a highly increased risk of intellectual disability was found for the deletion (IRR, 34.08; 95% CI, 22.39-49.27) and duplication (IRR, 33.86; 95% CI, 8.42-87.87). Furthermore, individuals with the 22q11.2 deletion had an increased risk of several psychiatric disorders under study, for example, pervasive developmental disorders (IRR, 9.45; 95% CI, 5.64-14.69) and childhood autism (IRR, 8.94; 95% CI, 3.21-19.23). Conclusions and Relevance: Individuals with the 22q11.2 deletion or duplication have a significantly increased risk of developing psychiatric disorders. Survival analysis of persons carrying either the 22q11.2 deletion or duplication provides estimates of direct clinical relevance useful to assist clinical ascertainment, genetic counseling, guidance of symptomatic monitoring, and early clinical intervention.

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes.

CONTEXT: Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease. OBJECTIVE: We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. DESIGN AND PARTICIPANTS: A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls. RESULTS: We discovered 11 associations between single-nucleotide polymorphisms and five distinct biomarkers at a study-wide P < 3.4 × 10(-7). Nine associations were novel: IL18: BIRC6, RAD17, MARVELD2; ferritin: F5; IGF binding protein 1: SERPING1, KLKB, GCKR, CELSR2, and heat shock 70-kDa protein 1B: CFH. Three of the identified loci (CELSR2, HNF1A, and GCKR) were significantly associated with T2D, of which the association with the CELSR2 locus has not been shown previously. CONCLUSION: The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes therapeutic strategies.

A glycogene mutation map for discovery of diseases of glycosylation.

Glycosylation of proteins and lipids involves over 200 known glycosyltransferases (GTs), and deleterious defects in many of the genes encoding these enzymes cause disorders collectively classified as congenital disorders of glycosylation (CDGs). Most known CDGs are caused by defects in glycogenes that affect glycosylation globally. Many GTs are members of homologous isoenzyme families and deficiencies in individual isoenzymes may not affect glycosylation globally. In line with this, there appears to be an underrepresentation of disease-causing glycogenes among these larger isoenzyme homologous families. However, genome-wide association studies have identified such isoenzyme genes as candidates for different diseases, but validation is not straightforward without biomarkers. Large-scale whole-exome sequencing (WES) provides access to mutations in, for example, GT genes in populations, which can be used to predict and/or analyze functional deleterious mutations. Here, we constructed a draft of a functional mutational map of glycogenes, GlyMAP, from WES of a rather homogenous population of 2000 Danes. We cataloged all missense mutations and used prediction algorithms, manual inspection and in case of carbohydrate-active enzymes family GT27 experimental analysis of mutations to map deleterious mutations. GlyMAP (http://glymap.glycomics.ku.dk) provides a first global view of the genetic stability of the glycogenome and should serve as a tool for discovery of novel CDGs.

Variation and association to diabetes in 2000 full mtDNA sequences mined from an exome study in a Danish population.

In this paper, we mine full mtDNA sequences from an exome capture data set of 2000 Danes, showing that it is possible to get high-quality full-genome sequences of the mitochondrion from this resource. The sample includes 1000 individuals with type 2 diabetes and 1000 controls. We characterise the variation found in the mtDNA sequence in Danes and relate the variation to diabetes risk as well as to several blood phenotypes of the controls but find no significant associations. We report 2025 polymorphisms, of which 393 have not been reported previously. These 393 mutations are both very rare and estimated to be caused by very recent mutations but individuals with type 2 diabetes do not possess more of these variants. Population genetics analysis using Bayesian skyline plot shows a recent history of rapid population growth in the Danish population in accordance with the fact that >40% of variable sites are observed as singletons.

Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes.

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m(2) and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.

Genetic risk score of 46 type 2 diabetes risk variants associates with changes in plasma glucose and estimates of pancreatic ß-cell function over 5 years of follow-up.

More than 40 genetic risk variants for type 2 diabetes have been validated. We aimed to test whether a genetic risk score associates with the incidence of type 2 diabetes and with 5-year changes in glycemic traits and whether the effects were modulated by changes in BMI and lifestyle. The Inter99 study population was genotyped for 46 variants, and a genetic risk score was constructed. During a median follow-up of 11 years, 327 of 5,850 individuals developed diabetes. Physical examinations and oral glucose tolerance tests were performed at baseline and after 5 years (n = 3,727). The risk of incident type 2 diabetes was increased with a hazard ratio of 1.06 (95% CI 1.03-1.08) per risk allele. While the population in general had improved glucose regulation during the 5-year follow-up period, each additional allele in the genetic risk score was associated with a relative increase in fasting, 30-min, and 120-min plasma glucose values and a relative decrease in measures of ß-cell function over the 5-year period, whereas indices of insulin sensitivity were unaffected. The effect of the genetic risk score on 5-year changes in fasting plasma glucose was stronger in individuals who increased their BMI. In conclusion, a genetic risk score based on 46 variants associated strongly with incident type 2 diabetes and 5-year changes in plasma glucose and ß-cell function. Individuals who gain weight may be more susceptible to the cumulative impact of type 2 diabetes risk variants on fasting plasma glucose.

Genetic architecture of vitamin B12 and folate levels uncovered applying deeply sequenced large datasets.

Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B(12) (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B(12) and folate measurements, respectively. We found six novel loci associating with serum B(12) (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B(12) and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimer's disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B(12) or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations.

Type 2 diabetes risk alleles near BCAR1 and in ANK1 associate with decreased ß-cell function whereas risk alleles near ANKRD55 and GRB14 associate with decreased insulin sensitivity in the Danish Inter99 cohort.

CONTEXT: Recently, 10 novel type 2 diabetes (T2D) susceptibility single nucleotide polymorphisms (SNPs) in ZMIZ1, ANK1, KLHDC5, TLE1, ANKRD55, CILP2, MC4R, BCAR1, HMG20A, and GRB14 loci were discovered in MetaboChip-genotyped populations of European ancestry. OBJECTIVE: The aim of the present study was to characterize prediabetic quantitative traits underlying these SNP associations and to calculate the amount of interindividual variation in glycemic traits explained by these and previous T2D susceptibility variants. DESIGN AND PARTICIPANTS: A total of 5739 Danish individuals naive to glucose-lowering medication were included in quantitative trait studies, and case-control analyses were performed in 1892 patients with T2D and 6603 normoglycemic control subjects. Participants without known T2D underwent an oral glucose tolerance test, and measures of insulin release and sensitivity were estimated from insulinogenic, disposition, BIGTT, and Matsuda indexes. RESULTS: We confirmed associations of ZMIZ1, KLHDC5, CILP2, HMG20A, ANK1, ANKRD55, and BCAR1 with T2D. The risk T allele of BCAR1 rs7202877 associated with decreased disposition index (P = .02). The C allele of ANK1 rs516946 associated with decreased insulinogenic (P = .005) and disposition (P = .002) indexes. The G allele of ANKRD55 rs459193 associated with decreased Matsuda index (P = .02) adjusted for waist circumference. The C allele of GRB14 rs13389219 associated with both increased insulinogenic (P = .04) and decreased Matsuda (P = .05) indexes. All validated European T2D variants still only explained a few percentage points of glycemic trait variation. CONCLUSIONS: BCAR1 rs7202877 may mediate its diabetogenic impact through impaired ß-cell function, but this finding needs to be replicated in independent studies. In addition, we substantiated previous evidence that ANK1 rs516946 confers impaired insulin release and that ANKRD55 rs459193 and GRB14 rs13389219 associate with insulin resistance.

Genetic variant SLC2A2 [corrected] Is associated with risk of cardiovascular disease ­ assessing the individual and cumulative effect of 46 type 2 diabetes related genetic variants.

AIM: To assess the individual and combined effect of 46 type 2 diabetes related risk alleles on incidence of a composite CVD endpoint. METHODS: Data from the first Danish MONICA study (N = 3523) and the Inter99 study (N = 6049) was used. Using Cox proportional hazard regression the individual effect of each risk allele on incident CVD was analyzed. Risk was presented as hazard ratios (HR) per risk allele. RESULTS: During 80,859 person years 1441 incident cases of CVD (fatal and non-fatal) occurred in the MONICA study. In Inter99 942 incident cases were observed during 61,239 person years. In the Danish MONICA study four gene variants were significantly associated with incident CVD independently of known diabetes status at baseline; SLC2A2 rs11920090 (HR 1.147, 95% CI 1.027-1.283 , P = 0.0154), C2CD4A rs7172432 (1.112, 1.027-1.205 , P = 0.0089), GCKR rs780094 (1.094, 1.007-1.188 , P = 0.0335) and C2CD4B rs11071657 (1.092, 1.007-1.183 , P = 0.0323). The genetic score was significantly associated with increased risk of CVD (1.025, 1.010-1.041, P = 0.0016). In Inter99 two gene variants were associated with risk of CVD independently of diabetes; SLC2A2 (HR 1.180, 95% CI 1.038-1.341 P = 0.0116) and FTO (0.909, 0.827-0.998, P = 0.0463). Analysing the two populations together we found SLC2A2 rs11920090 (HR 1.164, 95% CI 1.070-1.267, P = 0.0004) meeting the Bonferroni corrected threshold for significance. GCKR rs780094 (1.076, 1.010-1.146, P = 0.0229), C2CD4B rs11071657 (1.067, 1.003-1.135, P = 0.0385) and NOTCH2 rs10923931 (1.104 (1.001 ; 1.217 , P = 0.0481) were found associated with CVD without meeting the corrected threshold. The genetic score was significantly associated with increased risk of CVD (1.018, 1.006-1.031, P = 0.0043). CONCLUSIONS: This study showed that out of the 46 genetic variants examined only the minor risk allele of SLC2A2 rs11920090 was significantly (P = 0.0005) associated with a composite endpoint of incident CVD below the threshold for statistical significance corrected for multiple testing. This potential pathway needs further exploration.

The effect of FOXA2 rs1209523 on glucose-related phenotypes and risk of type 2 diabetes in Danish individuals.

BACKGROUND: Variations within the FOXA family have been studied for a putative contribution to the risk of type 2 diabetes (T2D), and recently the minor T-allele of FOXA2 rs1209523 was reported to associate with decreased fasting plasma glucose levels in a study using a weighted false discovery rate control procedure to enhance the statistical power of genome wide association studies in detecting associations between low-frequency variants and a given trait.Thus, the primary aim of this study was to investigate whether the minor T-allele of rs1205923 in FOXA2 associated with 1) decreased fasting plasma glucose and 2) a lower risk of developing T2D. Secondly, we investigated whether rs1205923 in FOXA2 associated with other glucose-related phenotypes. METHODS: The variant was genotyped in Danish individuals from four different study populations using KASPar(®) PCR SNP genotyping system. We examined for associations of the FOXA2 genotype with fasting plasma glucose and estimates of insulin release and insulin sensitivity following an oral glucose tolerance test in 6,162 Danish individuals from the population-based Inter99 study while association with T2D risk was assessed in 10,196 Danish individuals including four different study populations. RESULTS: The FOXA2 rs1209523 was not associated with fasting plasma glucose (effect size (ß) = -0.03 mmol/l (95%CI: -0.07; 0.01), p = 0.2) in glucose-tolerant individuals from the general Danish population. Furthermore, when employing a case-control setting the variant showed no association with T2D (odds ratio (OR) = 0.82 (95%CI: 0.62-1.07), p = 0.1) among Danish individuals. However, when we performed the analysis in a subset of 6,022 non-obese individuals (BMI < 30 kg/m(2)) an association with T2D was observed (OR = 0.68 (95%CI: 0.49-0.94), p = 0.02). Also, several indices of insulin release and ß-cell function were associated with the minor T-allele of FOXA2 rs1209523 in non-obese individuals. CONCLUSIONS: We failed to replicate association of the minor T-allele of FOXA2 rs1209523 with fasting plasma glucose in a population based sample of glucose tolerant individuals. More extensive studies are needed in order to fully elucidate the potential role of FOXA2 in glucose homeostasis.

Physiologic characterization of type 2 diabetes-related loci.

For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic ß-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches.

Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants.

Targeted capture combined with massively parallel exome sequencing is a promising approach to identify genetic variants implicated in human traits. We report exome sequencing of 200 individuals from Denmark with targeted capture of 18,654 coding genes and sequence coverage of each individual exome at an average depth of 12-fold. On average, about 95% of the target regions were covered by at least one read. We identified 121,870 SNPs in the sample population, including 53,081 coding SNPs (cSNPs). Using a statistical method for SNP calling and an estimation of allelic frequencies based on our population data, we derived the allele frequency spectrum of cSNPs with a minor allele frequency greater than 0.02. We identified a 1.8-fold excess of deleterious, non-syonomyous cSNPs over synonymous cSNPs in the low-frequency range (minor allele frequencies between 2% and 5%). This excess was more pronounced for X-linked SNPs, suggesting that deleterious substitutions are primarily recessive.