Genome-wide association studies (GWAS): impact on elucidating the aetiology of diabetes

Type 1 diabetes: genes associated with disease development

Type 1 diabetes (T1D) is the third most common autoimmune disease which develops due to genetic and environmental risk factors. Based on the World Health Organization (WHO) report from 2014 the number of people suffering from all types of diabetes ascended to 422 million, compared to 108 million in 1980. It was calculated that this number will double by the end of 2030. In 2015 American Diabetes Association (ADA) announced that 30.3 million Americans (that is 9.4% of the overall population) had diabetes of which only approximately 1.25 million had T1D. Nowadays, T1D represents roughly 10% of adult diabetes cases total. Multiple genetic abnormalities at different loci have been found to contribute to type 1 diabetes development. The analysis of genome-wide association studies (GWAS) of T1D has identified over 50 susceptible regions (and genes within these regions). Many of these regions are defined by single nucleotide polymorphisms (SNPs) but molecular mechanisms through which they increase or lower the risk of diabetes remain unknown. Genetic factors (in existence since birth) can be detected long before the emergence of immunological or clinical markers. Therefore, a comprehensive understanding of the multiple genetic factors underlying T1D is extremely important for further clinical trials and development of personalized medicine for diabetic patients. We present an overview of current studies and information about regions in the human genome associated with T1D. Moreover, we also put forward information about epigenetic modifications, non-coding RNAs and environmental factors involved in T1D development and onset.

Epigenetic modification and therapeutic targets of diabetes mellitus

The prevalence of diabetes and its related complications are increasing significantly globally. Collected evidence suggested that several genetic and environmental factors contribute to diabetes mellitus. Associated complications such as retinopathy, neuropathy, nephropathy and other cardiovascular complications are a direct result of diabetes. Epigenetic factors include deoxyribonucleic acid (DNA) methylation and histone post-translational modifications. These factors are directly related with pathological factors such as oxidative stress, generation of inflammatory mediators and hyperglycemia. These result in altered gene expression and targets cells in the pathology of diabetes mellitus without specific changes in a DNA sequence. Environmental factors and malnutrition are equally responsible for epigenetic states. Accumulated evidence suggested that environmental stimuli alter the gene expression that result in epigenetic changes in chromatin. Recent studies proposed that epigenetics may include the occurrence of ‘metabolic memory’ found in animal studies. Further study into epigenetic mechanism might give us new vision into the pathogenesis of diabetes mellitus and related complication thus leading to the discovery of new therapeutic targets. In this review, we discuss the possible epigenetic changes and mechanism that happen in diabetes mellitus type 1 and type 2 separately. We highlight the important epigenetic and non-epigenetic therapeutic targets involved in the management of diabetes and associated complications.

Post-transcriptional markers associated with clinical complications in Type 1 and Type 2 diabetes mellitus

The delayed diagnosis and the inadequate treatment of diabetes increase the risk of chronic complications. The study of regulatory molecules such as miRNAs can provide expression profiles of diabetes and diabetes complications. We evaluated the mononuclear cell miRNA profiles of 63 Type 1 and Type 2 diabetes patients presenting or not microvascular complications, and 40 healthy controls, using massive parallel sequencing. Gene targets, enriched pathways, dendograms and miRNA-mRNA networks were performed for the differentially expressed miRNAs. Six more relevant miRNAs were validated by RT-qPCR and data mining analysis. MiRNAs associated with specific complications included: i) neuropathy (miR-873-5p, miR-125a-5p, miR-145-3p and miR-99b-5p); ii) nephropathy (miR-1249-3p, miR-193a-5p, miR-409-5p, miR-1271-5p, miR-501-3p, miR-148b-3p and miR-9-5p); and iii) retinopathy (miR-143-3p, miR-1271-5p, miR-409-5p and miR-199a-5p). These miRNAs mainly targeted gene families and specific genes associated with advanced glycation end products and their receptors. Sets of miRNAs were also defined as potential targets for diabetes/diabetes complication pathogenesis.

Comparative analysis of mRNA expression profiles in Type 1 and Type 2 diabetes mellitus

Aim: We aimed to understand the individual and shared features of Type 1 diabetes (T1D) and Type 2 diabetes (T2D) by analyzing the gene expression profile. Materials & methods: An integrated analysis was performed with microarray datasets for T1D and T2D. Compared with normal control, shared and specific differentially expressed genes (DEGs) in T1D and T2D were obtained. Functional annotation, further validation and receiver operating characteristic curve analysis were performed. Results: Five and three datasets for T1D and T2D were downloaded, respectively. In total, 141 (85 T1D vs 56 normal controls) and 70 (29 T2D vs 41 normal controls) peripheral blood samples were included in T1D and T2D group, respectively. Compared with normal controls, 119 and 146 DEGs were found in T1D and T2D, respectively. PNP and CCR1 have great diagnostic value for both T1D and T2D. MGAM and NAMPT had great diagnostic value for T2D. Conclusion: Our finding provided clues for developing biomarkers for diabetes.

Heterogeneous impact of type 2 diabetes mellitus-related genetic variants on gestational glycemic traits: review and future research needs

Gestational glucose homeostasis influences mother's metabolic health, pregnancy outcomes, fetal development and offspring growth. To understand the genetic roles in pregnant glucose metabolism and genetic predisposition for gestational diabetes (GDM), we reviewed the recent literature up to Jan, 2018 and evaluated the influence of T2DM-related genetic variants on gestational glycemic traits and glucose tolerance. A total of 140 variants of 89 genes were integrated. Their associations with glycemic traits in and outside pregnancy were compared. The genetic circumstances underlying glucose metabolism exhibit a similarity between pregnant and non-pregnant populations. While, not all of the T2DM-associated genetic variants are related to pregnant glucose tolerance, such as genes involved in fasting insulin/C-peptide regulation. Some genetic variants may have distinct effects on gestational glucose homeostasis. And certain genes may be particularly involved in this process via specific mechanisms, such as HKDC1, MTNR1B, BACE2, genes encoding cell cycle regulators, adipocyte regulators, inflammatory factors and hepatic factors related to gestational glucose sensing and insulin signaling. However, it is currently difficult to evaluate these associations with quantitative synthesis due to inadequate data, different analytical methods, varied measurements for glycemic traits, controversies in diagnosis of GDM, and unknown ethnicity- and/or sex-related influences on pregnant maternal metabolism. In conclusion, different genetic associations with glycemic traits may exist between pregnant and non-pregnant conditions. Comprehensive research on specific genetic regulation in gestation is necessary.

T2DiACoD: A Gene Atlas of Type 2 Diabetes Mellitus Associated Complex Disorders

We performed integrative analysis of genes associated with type 2 Diabetes Mellitus (T2DM) associated complications by automated text mining with manual curation and also gene expression analysis from Gene Expression Omnibus. They were analysed for pathogenic or protective role, trends, interaction with risk factors, Gene Ontology enrichment and tissue wise differential expression. The database T2DiACoD houses 650 genes, and 34 microRNAs associated with T2DM complications. Seven genes AGER, TNFRSF11B, CRK, PON1, ADIPOQ, CRP and NOS3 are associated with all 5 complications. Several genes are studied in multiple years in all complications with high proportion in cardiovascular (75.8%) and atherosclerosis (51.3%). T2DM Patients' skeletal muscle tissues showed high fold change in differentially expressed genes. Among the differentially expressed genes, VEGFA is associated with several complications of T2DM. A few genes ACE2, ADCYAP1, HDAC4, NCF1, NFE2L2, OSM, SMAD1, TGFB1, BDNF, SYVN1, TXNIP, CD36, CYP2J2, NLRP3 with details of protective role are catalogued. Obesity is clearly a dominant risk factor interacting with the genes of T2DM complications followed by inflammation, diet and stress to variable extents. This information emerging from the integrative approach used in this work could benefit further therapeutic approaches. The T2DiACoD is available at www.http://t2diacod.igib.res.in/ .

PROTECTIVE EFFECT OF CAMEL MILK AS ANTI-DIABETIC SUPPLEMENT: BIOCHEMICAL, MOLECULAR AND IMMUNOHISTOCHEMICAL STUDY

Background:

Diabetes is a serious disease affects human health. Diabetes in advanced stages is accompanied by general weakness and alteration in fats and carbohydrates metabolism. Recently there are some scientific trends about the usage of camel milk (CM) in the treatment of diabetes and its associated alterations. CM contains vital active particles with insulin like action that cure diabetes and its complications but how these effects occur, still unclear.

Materials and Methods:

Seventy-five adult male rats of the albino type divided into five equal groups. Group 1 served as a negative control (C). Group 2 was supplemented with camel milk (CM). Diabetes was induced in the remaining groups (3, 4 and 5). Group 3 served as positive diabetic control (D). Group 4 served as diabetic and administered metformin (D+MET). Group 5 served as diabetes and supplemented with camel milk (D+CM). Camel milk was supplemented for two consecutive months. Serum glucose, leptin, insulin, liver, kidney, antioxidants, MDA and lipid profiles were assayed. Tissues from liver and adipose tissues were examined using RT-PCR analysis for the changes in mRNA expression of genes of carbohydrates and lipid metabolism. Pancreas and liver were used for immunohistochemical examination using specific antibodies.

Results:

Camel milk supplementation ameliorated serum biochemical measurements that altered after diabetes induction. CM supplementation up-regulated mRNA expression of IRS-2, PK, and FASN genes, while down-regulated the expression of CPT-1 to control mRNA expression level. CM did not affect the expression of PEPCK gene. On the other hand, metformin failed to reduce the expression of CPT-1 compared to camel milk administered rats. Immunohistochemical findings revealed that CM administration restored the immunostaining reactivity of insulin and GLUT-4 in the pancreas of diabetic rats.

Conclusion:

CM administration is of medical importance and helps physicians in the treatment of diabetes mellitus.

An Islet-Targeted Genome-Wide Association Scan Identifies Novel Genes Implicated in Cytokine-Mediated Islet Stress in Type 2 Diabetes

Genome-wide association studies in human type 2 diabetes (T2D) have renewed interest in the pancreatic islet as a contributor to T2D risk. Chronic low-grade inflammation resulting from obesity is a risk factor for T2D and a possible trigger of β-cell failure. In this study, microarray data were collected from mouse islets after overnight treatment with cytokines at concentrations consistent with the chronic low-grade inflammation in T2D. Genes with a cytokine-induced change of >2-fold were then examined for associations between single nucleotide polymorphisms and the acute insulin response to glucose (AIRg) using data from the Genetics Underlying Diabetes in Hispanics (GUARDIAN) Consortium. Significant evidence of association was found between AIRg and single nucleotide polymorphisms in Arap3 (5q31.3), F13a1 (6p25.3), Klhl6 (3q27.1), Nid1 (1q42.3), Pamr1 (11p13), Ripk2 (8q21.3), and Steap4 (7q21.12). To assess the potential relevance to islet function, mouse islets were exposed to conditions modeling low-grade inflammation, mitochondrial stress, endoplasmic reticulum (ER) stress, glucotoxicity, and lipotoxicity. RT-PCR revealed that one or more forms of stress significantly altered expression levels of all genes except Arap3. Thapsigargin-induced ER stress up-regulated both Pamr1 and Klhl6. Three genes confirmed microarray predictions of significant cytokine sensitivity: F13a1 was down-regulated 3.3-fold by cytokines, Ripk2 was up-regulated 1.5- to 3-fold by all stressors, and Steap4 was profoundly cytokine sensitive (167-fold up-regulation). Three genes were thus closely associated with low-grade inflammation in murine islets and also with a marker for islet function (AIRg) in a diabetes-prone human population. This islet-targeted genome-wide association scan identified several previously unrecognized candidate genes related to islet dysfunction during the development of T2D.

Genetics of type 2 diabetes-pitfalls and possibilities

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

Does the microbiota play a role in the pathogenesis of autoimmune diseases?

The microbiota of the human metaorganism is not a mere bystander. These microbes have coevolved with us and are pivotal to normal development and homoeostasis. Dysbiosis of the GI microbiota is associated with many disease susceptibilities, including obesity, malignancy, liver disease and GI pathology such as IBD. It is clear that there is direct and indirect crosstalk between this microbial community and host immune response. However, the precise mechanism of this microbial influence in disease pathogenesis remains elusive and is now a major research focus. There is emerging literature on the role of the microbiota in the pathogenesis of autoimmune disease, with clear and increasing evidence that changes in the microbiota are associated with some of these diseases. Examples include type 1 diabetes, coeliac disease and rheumatoid arthritis, and these contribute significantly to global morbidity and mortality. Understanding the role of the microbiota in autoimmune diseases may offer novel insight into factors that initiate and drive disease progression, stratify patient risk for complications and ultimately deliver new therapeutic strategies. This review summarises the current status on the role of the microbiota in autoimmune diseases.

Novel approaches to drug discovery for the treatment of type 2 diabetes

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a chronic, complex and multifactorial metabolic disorder, which has become a serious global health problem. The side effects of known drugs and the deficiency of long-term safety data, in addition to the already determined adverse effects for the current preclinical drugs against T2DM, have largely called upon the urgent exploration of novel therapeutic and preventative strategies against this disease.

AREAS COVERED

The authors highlight the potential approaches for anti-T2DM drug discovery by focusing on: the restoration of pancreatic β-cell mass, the promotion of insulin secretion, the regulation of oxidative stress and endoplasmic reticulum (ER) stress and the modulation of autophagy.

EXPERT OPINION

T2DM is based on the gradual development of insulin resistance and β-cell dysfunction. Thus, the restoration of β-cell function is considered as one of the promising therapeutic strategies against T2DM. The stress factors, such as oxidative stress, ER stress and autophagy, play potent roles in the regulation of β-cell apoptosis, insulin secretion and sensitivity in the development of T2DM involving complicated cross-talks. Based on multiplex stress-involved regulatory networks, more and more novel potential targets have been discovered and the multi-targeted drug leads are expected to help develop more effective clinical agents for the treatment of T2DM.

Integrative analysis of the transcriptome profiles observed in type 1, type 2 and gestational diabetes mellitus reveals the role of inflammation

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease, while type 2 (T2D) and gestational diabetes (GDM) are considered metabolic disturbances. In a previous study evaluating the transcript profiling of peripheral mononuclear blood cells obtained from T1D, T2D and GDM patients we showed that the gene profile of T1D patients was closer to GDM than to T2D. To understand the influence of demographical, clinical, laboratory, pathogenetic and treatment features on the diabetes transcript profiling, we performed an analysis integrating these features with the gene expression profiles of the annotated genes included in databases containing information regarding GWAS and immune cell expression signatures.

METHODS

Samples from 56 (19 T1D, 20 T2D, and 17 GDM) patients were hybridized to whole genome one-color Agilent 4x44k microarrays. Non-informative genes were filtered by partitioning, and differentially expressed genes were obtained by rank product analysis. Functional analyses were carried out using the DAVID database, and module maps were constructed using the Genomica tool.

RESULTS

The functional analyses were able to discriminate between T1D and GDM patients based on genes involved in inflammation. Module maps of differentially expressed genes revealed that modulated genes: i) exhibited transcription profiles typical of macrophage and dendritic cells; ii) had been previously associated with diabetic complications by association and by meta-analysis studies, and iii) were influenced by disease duration, obesity, number of gestations, glucose serum levels and the use of medications, such as metformin.

CONCLUSION

This is the first module map study to show the influence of epidemiological, clinical, laboratory, immunopathogenic and treatment features on the transcription profiles of T1D, T2D and GDM patients.

Association analysis of STK39, MCCC1/LAMP3 and sporadic PD in the Chinese Han population

With the completion of the Human Genome Project, GWAS have been widely used in exploring the genetic studies of complex diseases. A meta-analysis of datasets from five Parkinson's disease GWAS from the USA and Europe found 11 loci that surpassed the threshold for genome-wide significance (p<5×10(-8)), and five were newly identified loci (ACMSD, STK39, MCCC1/LAMP3, SYT11 and CCDC62/HIP1R). Another GWAS of the Ashkenazi Jewish population also identified loci in STK39 and LAMP3. Because the association between the STK39 and MCCC1/LAMP3 genes and PD was confirmed in different populations, we conducted a case-control cohort to clarify the association between the four single nucleotide polymorphism (SNP) loci (rs2102808 and rs3754775 in the STK39; rs11711441 and rs12493050 in the MCCC1/LAMP3) and PD in the Chinese Han population. Polymerase chain reaction and direct DNA sequencing analyses were used to detect the four variations in a case-control cohort comprised of 993 ethnic Chinese subjects. We found that in the detection of the rs11711441, there was a significant difference between ungrouped populations, early-onset PD, late-onset PD, male PD, female PD and the corresponding control group in allele and genotype frequency (p<0.001, OR<1). In the detection of the rs2102808, rs3754775 and rs12493050, ungrouped populations, early-onset PD, late-onset PD, male PD or female PD with the corresponding control group showed no significant difference in allele and genotype frequency (p>0.0125). Our findings suggested that the allele G of rs11711441 of the MCCC1/LAMP3 gene can decrease the risk of PD in Chinese population. No statistically significant difference in genotype frequency between cases and controls was observed for the other three SNPs.

Genetic and epigenetic factors in etiology of diabetes mellitus type 1

Diabetes mellitus type 1 (T1D) is a complex disease resulting from the interplay of genetic, epigenetic, and environmental factors. Recent progress in understanding the genetic basis of T1D has resulted in an increased recognition of childhood diabetes heterogeneity. After the initial success of family-based linkage analyses, which uncovered the strong linkage and association between HLA gene variants and T1D, genome-wide association studies performed with high-density single-nucleotide polymorphism genotyping platforms provided evidence for a number of novel loci, although fine mapping and characterization of these new regions remains to be performed. T1D is one of the most heritable common diseases, and among autoimmune diseases it has the largest range of concordance rates in monozygotic twins. This fact, coupled with evidence of various epigenetic modifications of gene expression, provides convincing proof of the complex interplay between genetic and environmental factors. In T1D, epigenetic phenomena, such as DNA methylation, histone modifications, and microRNA dysregulation, have been associated with altered gene expression. Increasing epidemiologic and experimental evidence supports the role of genetic and epigenetic alterations in the etiopathology of diabetes. We discuss recent results related to the role of genetic and epigenetic factors involved in development of T1D.

Complex disease interventions from a network model for type 2 diabetes

There is accumulating evidence that the proteins encoded by the genes associated with a common disorder interact with each other, participate in similar pathways and share GO terms. It has been anticipated that the functional modules in a disease related functional linkage network are informative to reveal significant metabolic processes and disease's associations with other complex disorders. In the current study, Type 2 diabetes associated functional linkage network (T2DFN) containing 2770 proteins and 15041 linkages was constructed. The functional modules in this network were scored and evaluated in terms of shared pathways, co-localization, co-expression and associations with similar diseases. The assembly of top scoring overlapping members in the functional modules revealed that, along with the well known biological pathways, circadian rhythm, diverse actions of nuclear receptors in steroid and retinoic acid metabolisms have significant occurrence in the pathophysiology of the disease. The disease's association with other metabolic and neuromuscular disorders was established through shared proteins. Nuclear receptor NRIP1 has a pivotal role in lipid and carbohydrate metabolism, indicating the need to investigate subsequent effects of NRIP1 on Type 2 diabetes. Our study also revealed that CREB binding protein (CREBBP) and cardiotrophin-1 (CTF1) have suggestive roles in linking Type 2 diabetes and neuromuscular diseases.

The genomic signature of trait-associated variants

BACKGROUND

Genome-wide association studies have identified thousands of SNP variants associated with hundreds of phenotypes. For most associations the causal variants and the molecular mechanisms underlying pathogenesis remain unknown. Exploration of the underlying functional annotations of trait-associated loci has thrown some light on their potential roles in pathogenesis. However, there are some shortcomings of the methods used to date, which may undermine efforts to prioritize variants for further analyses. Here, we introduce and apply novel methods to rigorously identify annotation classes showing enrichment or depletion of trait-associated variants taking into account the underlying associations due to co-location of different functional annotations and linkage disequilibrium.

RESULTS

We assessed enrichment and depletion of variants in publicly available annotation classes such as genic regions, regulatory features, measures of conservation, and patterns of histone modifications. We used logistic regression to build a multivariate model that identified the most influential functional annotations for trait-association status of genome-wide significant variants. SNPs associated with all of the enriched annotations were 8 times more likely to be trait-associated variants than SNPs annotated with none of them. Annotations associated with chromatin state together with prior knowledge of the existence of a local expression QTL (eQTL) were the most important factors in the final logistic regression model. Surprisingly, despite the widespread use of evolutionary conservation to prioritize variants for study we find only modest enrichment of trait-associated SNPs in conserved regions.

CONCLUSION

We established odds ratios of functional annotations that are more likely to contain significantly trait-associated SNPs, for the purpose of prioritizing GWAS hits for further studies. Additionally, we estimated the relative and combined influence of the different genomic annotations, which may facilitate future prioritization methods by adding substantial information.

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

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

A noncoding RNA antisense to moesin at 5p14.1 in autism

People with autism spectrum disorder (ASD) are characterized by deficits in social interaction, language, and behavioral flexibility. Rare mutations and copy number variations have been identified in individuals with ASD, but in most patients, the causal variants remain unknown. A genome-wide association study (GWAS), designed to identify genes and pathways that contribute to ASD, indicated a genome-wide significant association of ASD with the single-nucleotide polymorphism (SNP) rs4307059 (P = 10⁻¹⁰), which is located in a gene-poor region of chromosome 5p14.1. We describe here a 3.9-kb noncoding RNA that is transcribed from the region of the chromosome 5p14.1 ASD GWAS association SNP. The noncoding RNA was encoded by the opposite (antisense) strand of moesin pseudogene 1 (MSNP1), and we therefore designated it as MSNP1AS (moesin pseudogene 1, antisense). Chromosome 5p14.1 MSNP1AS was 94% identical and antisense to the X chromosome transcript of MSN, which encodes a protein (moesin) that regulates neuronal architecture. Individuals who carry the ASD-associated rs4307059 T allele showed increased expression of MSNP1AS. The MSNP1AS noncoding RNA bound to MSN, was highly overexpressed (12.7-fold) in postmortem cerebral cortex of individuals with ASD, and could regulate levels of moesin protein in human cell lines. These data reveal a biologically functional element that may contribute to ASD risk.

A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple Loci implicated in sex steroid hormone regulation

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Identification of cis-regulatory variation influencing protein abundance levels in human plasma

Proteins are central to almost all cellular processes, and dysregulation of expression and function is associated with a range of disorders. A number of studies in human have recently shown that genetic factors significantly contribute gene expression variation. In contrast, very little is known about the genetic basis of variation in protein abundance in man. Here, we assayed the abundance levels of proteins in plasma from 96 elderly Europeans using a new aptamer-based proteomic technology and performed genome-wide local (cis-) regulatory association analysis to identify protein quantitative trait loci (pQTL). We detected robust cis-associations for 60 proteins at a false discovery rate of 5%. The most highly significant single nucleotide polymorphism detected was rs7021589 (false discovery rate, 2.5 × 10(-12)), mapped within the gene coding sequence of Tenascin C (TNC). Importantly, we identified evidence of cis-regulatory variation for 20 previously disease-associated genes encoding protein, including variants with strong evidence of disease association show significant association with protein abundance levels. These results demonstrate that common genetic variants contribute to the differences in protein abundance levels in human plasma. Identification of pQTLs will significantly enhance our ability to discover and comprehend the biological and functional consequences of loci identified from genome-wide association study of complex traits. This is the first large-scale genetic association study of proteins in plasma measured using a novel, highly multiplexed slow off-rate modified aptamer (SOMAmer) proteomic platform.

Stem cell approaches for diabetes: towards beta cell replacement

Stem cells hold great promise for pancreatic beta cell replacement therapy for diabetes. In type 1 diabetes, beta cells are mostly destroyed, and in type 2 diabetes beta cell numbers are reduced by 40% to 60%. The proof-of-principle that cellular transplants of pancreatic islets, which contain insulin-secreting beta cells, can reverse the hyperglycemia of type 1 diabetes has been established, and there is now a need to find an adequate source of islet cells. Human embryonic stem cells can be directed to become fully developed beta cells and there is expectation that induced pluripotent stem (iPS) cells can be similarly directed. iPS cells can also be generated from patients with diabetes to allow studies of the genomics and pathogenesis of the disease. Some alternative approaches for replacing beta cells include finding ways to enhance the replication of existing beta cells, stimulating neogenesis (the formation of new islets in postnatal life), and reprogramming of pancreatic exocrine cells to insulin-producing cells. Stem-cell-based approaches could also be used for modulation of the immune system in type 1 diabetes, or to address the problems of obesity and insulin resistance in type 2 diabetes. Herein, we review recent advances in our understanding of diabetes and beta cell biology at the genomic level, and we discuss how stem-cell-based approaches might be used for replacing beta cells and for treating diabetes.