Anna Pluzhnikov

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.

Rational Inferences about Departures from Hardy-Weinberg Equilibrium

Previous studies have explored the use of departure from Hardy-Weinberg equilibrium (DHW) for fine mapping Mendelian disorders and for general fine mapping. Other studies have used Hardy-Weinberg tests for genotyping quality control. To enable investigators to make rational decisions about whether DHW is due to genotyping error or to underlying biology, we developed an analytic framework and software to determine the parameter values for which DHW might be expected for common diseases. We show analytically that, for a general disease model, the difference between population and Hardy-Weinberg expected genotypic frequencies (delta) at the susceptibility locus is a function of the susceptibility-allele frequency (q), heterozygote relative risk (beta), and homozygote relative risk (gamma). For unaffected control samples, is a function of risk in nonsusceptible homozygotes (alpha), the population prevalence of disease (KP), q, beta, and gamma. We used these analytic functions to calculate and the number of cases or controls needed to detect DHW for a range of genetic models consistent with common diseases (1.1 < or = gamma < or = 10 and 0.005 < or = KP < or = 0.2). Results suggest that significant DHW can be expected in relatively small samples of patients over a range of genetic models. We also propose a goodness-of-fit test to aid investigators in determining whether a DHW observed in the context of a case-control study is consistent with a genetic disease model. We illustrate how the analytic framework and software can be used to help investigators interpret DHW in the context of association studies of common diseases.

Clonally expanded mtDNA point mutations are abundant in individual cells of human tissues

Using single-cell sequence analysis, we discovered that a high proportion of cells in tissues as diverse as buccal epithelium and heart muscle contain high proportions of clonal mutant mtDNA expanded from single initial mutant mtDNA molecules. We demonstrate that intracellular clonal expansion of somatic point mutations is a common event in normal human tissues. This finding implies efficient homogenization of mitochondrial genomes within individual cells. Significant qualitative differences observed between the spectra of clonally expanded mutations in proliferating epithelial cells and postmitotic cardiomyocytes suggest, however, that either the processes generating these mutations or mechanisms driving them to homoplasmy are likely to be fundamentally different between the two tissues. Furthermore, the ability of somatic mtDNA mutations to expand (required for their phenotypic expression), as well as their apparently high incidence, reinforces the possibility that these mutations may be involved actively in various physiological processes such as aging and degenerative disease. The abundance of clonally expanded point mutations in individual cells of normal tissues also suggests that the recently discovered accumulation of mtDNA mutations in tumors may be explained by processes that are similar or identical to those operating in the normal tissue.

Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study

Summary Background VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. Methods We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort. Findings The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement). Interpretation A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population. Funding National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.

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 Tourette's syndrome

Tourettes syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (P<5 × 10−8); the top signal was found in rs7868992 on chromosome 9q32 within COL27A1 (P=1.85 × 10−6). A secondary analysis including an additional 211 cases and 285 controls from two closely related Latin American population isolates from the Central Valley of Costa Rica and Antioquia, Colombia also identified rs7868992 as the top signal (P=3.6 × 10−7 for the combined sample of 1496 cases and 5249 controls following imputation with 1000 Genomes data). This study lays the groundwork for the eventual identification of common TS susceptibility variants in larger cohorts and helps to provide a more complete understanding of the full genetic architecture of this disorder.

Genomewide Significant Linkage to Stuttering on Chromosome 12

Stuttering is a common and sometimes severe communication disorder, of unknown primary etiology, that exists in populations worldwide. Many types of evidence suggest a genetic contribution to stuttering; however, the complex inheritance of this disorder has hindered identification of these factors. We have employed highly inbred families to increase the power of linkage analysis of this disorder. Forty-four Pakistani families with documented or probable consanguinity, from the city of Lahore and surrounding areas, were included. Each family contained multiple cases of stuttering, which were diagnosed using the Stuttering Severity Instrument. Using the Marshfield Weber 9 marker panel, we performed a genomewide linkage scan focused on affected individuals and their parents. The analysis included 199 genotyped individuals, 144 affected and 55 unaffected. The Pedigree Relationship Statistical Test (PREST) was used to identify pedigrees that required additional specification of inbreeding. Initial nonparametric analysis gave evidence of linkage on chromosomes 1, 5, 7, and 12. Additional genotyping was performed on chromosome 12 to a 5-cM level of resolution, and 16 additional individuals were then included, bringing the number of families to 46. Analysis of the enlarged data set provided consistent evidence of linkage on chromosome 12: the S(homoz) scoring function gave a nonparametric LOD score of 4.61, and a LOD score of 3.51 was obtained using the S(all) scoring function. These results suggest that a locus on chromosome 12q may contain a gene with a large effect in this sample.

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.

Identification of HKDC1 and BACE2 as Genes Influencing Glycemic Traits During Pregnancy Through Genome-Wide Association Studies

Maternal metabolism during pregnancy impacts the developing fetus, affecting offspring birth weight and adiposity. This has important implications for metabolic health later in life (e.g., offspring of mothers with pre-existing or gestational diabetes mellitus have an increased risk of metabolic disorders in childhood). To identify genetic loci associated with measures of maternal metabolism obtained during an oral glucose tolerance test at ∼28 weeks’ gestation, we performed a genome-wide association study of 4,437 pregnant mothers of European (n = 1,367), Thai (n = 1,178), Afro-Caribbean (n = 1,075), and Hispanic (n = 817) ancestry, along with replication of top signals in three additional European ancestry cohorts. In addition to identifying associations with genes previously implicated with measures of glucose metabolism in nonpregnant populations, we identified two novel genome-wide significant associations: 2-h plasma glucose and HKDC1, and fasting C-peptide and BACE2. These results suggest that the genetic architecture underlying glucose metabolism may differ, in part, in pregnancy.