Jennifer E. Below

Germline BAP1 mutations predispose to malignant mesothelioma

Because only a small fraction of asbestos-exposed individuals develop malignant mesothelioma, and because mesothelioma clustering is observed in some families, we searched for genetic predisposing factors. We discovered germline mutations in the gene encoding BRCA1 associated protein-1 (BAP1) in two families with a high incidence of mesothelioma, and we observed somatic alterations affecting BAP1 in familial mesotheliomas, indicating biallelic inactivation. In addition to mesothelioma, some BAP1 mutation carriers developed uveal melanoma. We also found germline BAP1 mutations in 2 of 26 sporadic mesotheliomas; both individuals with mutant BAP1 were previously diagnosed with uveal melanoma. We also observed somatic truncating BAP1 mutations and aberrant BAP1 expression in sporadic mesotheliomas without germline mutations. These results identify a BAP1-related cancer syndrome that is characterized by mesothelioma and uveal melanoma. We hypothesize that other cancers may also be involved and that mesothelioma predominates upon asbestos exposure. These findings will help to identify individuals at high risk of mesothelioma who could be targeted for early intervention.

Insulin gene mutations as a cause of permanent neonatal diabetes

We report 10 heterozygous mutations in the human insulin gene in 16 probands with neonatal diabetes. A combination of linkage and a candidate gene approach in a family with four diabetic members led to the identification of the initial INS gene mutation. The mutations are inherited in an autosomal dominant manner in this and two other small families whereas the mutations in the other 13 patients are de novo. Diabetes presented in probands at a median age of 9 weeks, usually with diabetic ketoacidosis or marked hyperglycemia, was not associated with β cell autoantibodies, and was treated from diagnosis with insulin. The mutations are in critical regions of the preproinsulin molecule, and we predict that they prevent normal folding and progression of proinsulin in the insulin secretory pathway. The abnormally folded proinsulin molecule may induce the unfolded protein response and undergo degradation in the endoplasmic reticulum, leading to severe endoplasmic reticulum stress and potentially β cell death by apoptosis. This process has been described in both the Akita and Munich mouse models that have dominant-acting missense mutations in the Ins2 gene, leading to loss of β cell function and mass. One of the human mutations we report here is identical to that in the Akita mouse. The identification of insulin mutations as a cause of neonatal diabetes will facilitate the diagnosis and possibly, in time, treatment of this disorder.

Identification of Type 2 Diabetes Genes in Mexican Americans Through Genome-wide Association Studies

OBJECTIVE—The objective of this study was to identify DNA polymorphisms associated with type 2 diabetes in a Mexican-American population. RESEARCH DESIGN AND METHODS—We genotyped 116,204 single nucleotide polymorphisms (SNPs) in 281 Mexican Americans with type 2 diabetes and 280 random Mexican Americans from Starr County, Texas, using the Affymetrix GeneChip Human Mapping 100K set. Allelic association exact tests were calculated. Our most significant SNPs were compared with results from other type 2 diabetes genome-wide association studies (GWASs). Proportions of African, European, and Asian ancestry were estimated from the HapMap samples using structure for each individual to rule out spurious association due to population substructure. RESULTS—We observed more significant allelic associations than expected genome wide, as empirically assessed by permutation (14 below a P of 1 × 10−4 [8.7 expected]). No significant differences were observed between the proportion of ancestry estimates in the case and random control sets, suggesting that the association results were not likely confounded by substructure. A query of our top ∼1% of SNPs (P < 0.01) revealed SNPs in or near four genes that showed evidence for association (P < 0.05) in multiple other GWAS interrogated: rs979752 and rs10500641 near UBQLNL and OR52H1 on chromosome 11, rs2773080 and rs3922812 in or near RALGPS2 on chromosome 1, and rs1509957 near EGR2 on chromosome 10. CONCLUSIONS—We identified several SNPs with suggestive evidence for replicated association with type 2 diabetes that merit further investigation.

Genome-wide association study of type 2 diabetes in a sample from Mexico City and a meta-analysis of a Mexican-American sample from Starr County, Texas

Aims/hypothesisWe report a genome-wide association study of type 2 diabetes in an admixed sample from Mexico City and describe the results of a meta-analysis of this study and another genome-wide scan in a Mexican-American sample from Starr County, TX, USA. The top signals observed in this meta-analysis were followed up in the Diabetes Genetics Replication and Meta-analysis Consortium (DIAGRAM) and DIAGRAM+ datasets.MethodsWe analysed 967 cases and 343 normoglycaemic controls. The samples were genotyped with the Affymetrix Genome-wide Human SNP array 5.0. Associations of genotyped and imputed markers with type 2 diabetes were tested using a missing data likelihood score test. A fixed-effects meta-analysis including 1,804 cases and 780 normoglycaemic controls was carried out by weighting the effect estimates by their inverse variances.ResultsIn the meta-analysis of the two Hispanic studies, markers showing suggestive associations (p < 10−5) were identified in two known diabetes genes, HNF1A and KCNQ1, as well as in several additional regions. Meta-analysis of the two Hispanic studies and the recent DIAGRAM+ dataset identified genome-wide significant signals (p < 5 × 10−8) within or near the genes HNF1A and CDKN2A/CDKN2B, as well as suggestive associations in three additional regions, IGF2BP2, KCNQ1 and the previously unreported C14orf70.Conclusions/interpretationWe observed numerous regions with suggestive associations with type 2 diabetes. Some of these signals correspond to regions described in previous studies. However, many of these regions could not be replicated in the DIAGRAM datasets. It is critical to carry out additional studies in Hispanic and American Indian populations, which have a high prevalence of type 2 diabetes.

Genome-wide Meta-analysis for Severe Diabetic Retinopathy

Diabetic retinopathy is a leading cause of blindness. The purpose of this study is to identify novel genetic loci associated with the sight threatening complications of diabetic retinopathy. We performed a meta-analysis of genome-wide association data for severe diabetic retinopathy as defined by diabetic macular edema or proliferative diabetic retinopathy in unrelated cases ascertained from two large, type I diabetic cohorts: the Genetics of Kidney in Diabetes (GoKinD) and the Epidemiology of Diabetes Intervention and Control Trial (EDIC) studies. Controls were other diabetic subjects in the cohort. A combined total of 2829 subjects (973 cases, 1856 controls) were studied on 2 543 887 single nucleotide polymorphisms (SNPs). Subjects with nephropathy were excluded in a sub-analysis of 281 severe retinopathy cases. We also performed an association analysis of 1390 copy number variations (CNVs) using tag SNPs. No associations were significant at a genome-wide level after correcting for multiple measures. The meta-analysis did identify several associations that can be pursued in future replication studies, including an intergenic SNP, rs476141, on chromosome 1 (P-value 1.2 × 10(-7)). The most interesting signal from the CNV analysis came from the sub-group analysis without nephropathy subjects and is rs10521145 (P-value 3.4 × 10(-6)) in the intron of CCDC101, a histone acetyltransferase. This SNP tags the copy number region CNVR6685.1 on chromosome 16 at 28.5 Mb, a gain/loss site. In summary, this study nominates several novel genetic loci associated with the sight-threatening complications of diabetic retinopathy and anticipates future large-scale consortium-based validation studies.

A Genome-Wide Association Study Identifies a Novel Major Locus for Glycemic Control in Type 1 Diabetes, as Measured by Both A1C and Glucose

OBJECTIVE Glycemia is a major risk factor for the development of long-term complications in type 1 diabetes; however, no specific genetic loci have been identified for glycemic control in individuals with type 1 diabetes. To identify such loci in type 1 diabetes, we analyzed longitudinal repeated measures of A1C from the Diabetes Control and Complications Trial. RESEARCH DESIGN AND METHODS We performed a genome-wide association study using the mean of quarterly A1C values measured over 6.5 years, separately in the conventional (n = 667) and intensive (n = 637) treatment groups of the DCCT. At loci of interest, linear mixed models were used to take advantage of all the repeated measures. We then assessed the association of these loci with capillary glucose and repeated measures of multiple complications of diabetes. RESULTS We identified a major locus for A1C levels in the conventional treatment group near SORCS1 (10q25.1, P = 7 × 10−10), which was also associated with mean glucose (P = 2 × 10−5). This was confirmed using A1C in the intensive treatment group (P = 0.01). Other loci achieved evidence close to genome-wide significance: 14q32.13 (GSC) and 9p22 (BNC2) in the combined treatment groups and 15q21.3 (WDR72) in the intensive group. Further, these loci gave evidence for association with diabetic complications, specifically SORCS1 with hypoglycemia and BNC2 with renal and retinal complications. We replicated the SORCS1 association in Genetics of Diabetes in Kidneys (GoKinD) study control subjects (P = 0.01) and the BNC2 association with A1C in nondiabetic individuals. CONCLUSIONS A major locus for A1C and glucose in individuals with diabetes is near SORCS1. This may influence the design and analysis of genetic studies attempting to identify risk factors for long-term diabetic complications.

Genome-wide association and meta-analysis in populations from Starr County, Texas, and Mexico City identify type 2 diabetes susceptibility loci and enrichment for expression quantitative trait loci in top signals

Aims/hypothesisWe conducted genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) analyses to identify and characterise risk loci for type 2 diabetes in Mexican-Americans from Starr County, TX, USA.MethodUsing 1.8 million directly interrogated and imputed genotypes in 837 unrelated type 2 diabetes cases and 436 normoglycaemic controls, we conducted Armitage trend tests. To improve power in this population with high disease rates, we also performed ordinal regression including an intermediate class with impaired fasting glucose and/or glucose tolerance. These analyses were followed by meta-analysis with a study of 967 type 2 diabetes cases and 343 normoglycaemic controls from Mexico City, Mexico.ResultThe top signals (unadjusted p value <1 × 10−5) included 49 single nucleotide polymorphisms (SNPs) in eight gene regions (PER3, PARD3B, EPHA4, TOMM7, PTPRD, HNT [also known as RREB1], LOC729993 and IL34) and six intergenic regions. Among these was a missense polymorphism (rs10462020; Gly639Val) in the clock gene PER3, a system recently implicated in diabetes. We also report a second signal (minimum p value 1.52 × 10−6) within PTPRD, independent of the previously implicated SNP, in a population of Han Chinese. Top meta-analysis signals included known regions HNF1A and KCNQ1. Annotation of top association signals in both studies revealed a marked excess of trans-acting eQTL in both adipose and muscle tissues.Conclusions/InterpretationIn the largest study of type 2 diabetes in Mexican populations to date, we identified modest associations of novel and previously reported SNPs. In addition, in our top signals we report significant excess of SNPs that predict transcript levels in muscle and adipose tissues.

Spoiling the Whole Bunch: Quality Control Aimed at Preserving the Integrity of High-Throughput Genotyping

False-positive or false-negative results attributable to undetected genotyping errors and confounding factors present a constant challenge for genome-wide association studies (GWAS) given the low signals associated with complex phenotypes and the noise associated with high-throughput genotyping. In the context of the genetics of kidneys in diabetes (GoKinD) study, we identify a source of error in genotype calling and demonstrate that a standard battery of quality-control (QC) measures is not sufficient to detect and/or correct it. We show that, if genotyping and calling are done by plate (batch), even a few DNA samples of marginally acceptable quality can profoundly alter the allele calls for other samples on the plate. In turn, this leads to significant differential bias in estimates of allele frequency between plates and, potentially, to false-positive associations, particularly when case and control samples are not sufficiently randomized to plates. This problem may become widespread as investigators tap into existing public databases for GWAS control samples. We describe how to detect and correct this bias by utilizing additional sources of information, including raw signal-intensity data.

Mutations in ECEL1 Cause Distal Arthrogryposis Type 5D

Distal arthrogryposis (DA) syndromes are the most common of the heritable congenital-contracture disorders, and ~50% of cases are caused by mutations in genes that encode contractile proteins of skeletal myofibers. DA type 5D (DA5D) is a rare, autosomal-recessive DA previously defined by us and is characterized by congenital contractures of the hands and feet, along with distinctive facial features, including ptosis. We used linkage analysis and whole-genome sequencing of a multiplex consanguineous family to identify in endothelin-converting enzyme-like 1 (ECEL1) mutations that result in DA5D. Evaluation of a total of seven families affected by DA5D revealed in five families ECEL1 mutations that explain ~70% of cases overall. ECEL1 encodes a neuronal endopeptidase and is expressed in the brain and peripheral nerves. Mice deficient in Ecel1 exhibit perturbed terminal branching of motor neurons to the endplate of skeletal muscles, resulting in poor formation of the neuromuscular junction. Our results distinguish a second developmental pathway that causes congenital-contracture syndromes.

Whole-Genome Analysis Reveals that Mutations in Inositol Polyphosphate Phosphatase-like 1 Cause Opsismodysplasia

Opsismodysplasia is a rare, autosomal-recessive skeletal dysplasia characterized by short stature, characteristic facial features, and in some cases severe renal phosphate wasting. We used linkage analysis and whole-genome sequencing of a consanguineous trio to discover that mutations in inositol polyphosphate phosphatase-like 1 (INPPL1) cause opsismodysplasia with or without renal phosphate wasting. Evaluation of 12 families with opsismodysplasia revealed that INPPL1 mutations explain ~60% of cases overall, including both of the families in our cohort with more than one affected child and 50% of the simplex cases.