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author:("balech, plana")
1.  Correlation of rare coding variants in the gene encoding human glucokinase regulatory protein with phenotypic, cellular, and kinetic outcomes 
Defining the genetic contribution of rare variants to common diseases is a major basic and clinical science challenge that could offer new insights into disease etiology and provide potential for directed gene- and pathway-based prevention and treatment. Common and rare nonsynonymous variants in the GCKR gene are associated with alterations in metabolic traits, most notably serum triglyceride levels. GCKR encodes glucokinase regulatory protein (GKRP), a predominantly nuclear protein that inhibits hepatic glucokinase (GCK) and plays a critical role in glucose homeostasis. The mode of action of rare GCKR variants remains unexplored. We identified 19 nonsynonymous GCKR variants among 800 individuals from the ClinSeq medical sequencing project. Excluding the previously described common missense variant p.Pro446Leu, all variants were rare in the cohort. Accordingly, we functionally characterized all variants to evaluate their potential phenotypic effects. Defects were observed for the majority of the rare variants after assessment of cellular localization, ability to interact with GCK, and kinetic activity of the encoded proteins. Comparing the individuals with functional rare variants to those without such variants showed associations with lipid phenotypes. Our findings suggest that, while nonsynonymous GCKR variants, excluding p.Pro446Leu, are rare in individuals of mixed European descent, the majority do affect protein function. In sum, this study utilizes computational, cell biological, and biochemical methods to present a model for interpreting the clinical significance of rare genetic variants in common disease.
PMCID: PMC3248284  PMID: 22182842
2.  Predicting Diabetic Nephropathy Using a Multifactorial Genetic Model 
PLoS ONE  2011;6(4):e18743.
The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction.
Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random “training” (75%) and “test” (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients.
The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672) better than a model based on conventional variables only (C = 0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (χ2 = 17.79, p<0.0001). In the replication dataset, the model based on conventional variables only was not associated with nephropathy (χ2 = 3.2673, p = 0.07).
In this proof-of-concept study, we developed and validated a genetic model in the Ashkenazi/Sephardic population predicting nephropathy more effectively than a similarly constructed non-genetic model. Further testing is required to determine if this modeling approach, using an optimally selected panel of genetic markers, can provide clinically useful prediction and if generic models can be developed for use across multiple ethnic groups or if population-specific models are required.
PMCID: PMC3077408  PMID: 21533139
3.  Gene-Gene Interactions Lead to Higher Risk for Development of Type 2 Diabetes in an Ashkenazi Jewish Population 
PLoS ONE  2010;5(3):e9903.
Evidence has accumulated that multiple genetic and environmental factors play important roles in determining susceptibility to type 2 diabetes (T2D). Although variants from candidate genes have become prime targets for genetic analysis, few studies have considered their interplay. Our goal was to evaluate interactions among SNPs within genes frequently identified as associated with T2D.
Methods/Principal Findings
Logistic regression was used to study interactions among 4 SNPs, one each from HNF4A[rs1884613], TCF7L2[rs12255372], WFS1[rs10010131], and KCNJ11[rs5219] in a case-control Ashkenazi sample of 974 diabetic subjects and 896 controls. Nonparametric multifactor dimensionality reduction (MDR) and generalized MDR (GMDR) were used to confirm findings from the logistic regression analysis. HNF4A and WFS1 SNPs were associated with T2D in logistic regression analyses [P<0.0001, P<0.0002, respectively]. Interaction between these SNPs were also strong using parametric or nonparametric methods: the unadjusted odds of being affected with T2D was 3 times greater in subjects with the HNF4A and WFS1 risk alleles than those without either (95% CI = [1.7–5.3]; P≤0.0001). Although the univariate association between the TCF7L2 SNP and T2D was relatively modest [P = 0.02], when paired with the HNF4A SNP, the OR for subjects with risk alleles in both SNPs was 2.4 [95% CI = 1.7–3.4; P≤0.0001]. The KCNJ11 variant reached significance only when paired with either the HNF4A or WFSI SNPs: unadjusted ORs were 2.0 [95% CI = 1.4–2.8; P≤0.0001] and 2.3 [95% CI = 1.2-4.4; P≤0.0001], respectively. MDR and GMDR results were consistent with the parametric findings.
These results provide evidence of strong independent associations between T2D and SNPs in HNF4A and WFS1 and their interaction in our Ashkenazi sample. We also observed an interaction in the nonparametric analysis between the HNF4A and KCNJ11 SNPs (P≤0.001), demonstrating that an independently non-significant variant may interact with another variant resulting in an increased disease risk.
PMCID: PMC2845632  PMID: 20361036
4.  Parental diabetes status reveals association of mitochondrial DNA haplogroup J1 with type 2 diabetes 
BMC Medical Genetics  2009;10:60.
Although mitochondrial dysfunction is consistently manifested in patients with Type 2 Diabetes mellitus (T2DM), the association of mitochondrial DNA (mtDNA) sequence variants with T2DM varies among populations. These differences might stem from differing environmental influences among populations. However, other potentially important considerations emanate from the very nature of mitochondrial genetics, namely the notable high degree of partitioning in the distribution of human mtDNA variants among populations, as well as the interaction of mtDNA and nuclear DNA-encoded factors working in concert to govern mitochondrial function. We hypothesized that association of mtDNA genetic variants with T2DM could be revealed while controlling for the effect of additional inherited factors, reflected in family history information.
To test this hypothesis we set out to investigate whether mtDNA genetic variants will be differentially associated with T2DM depending on the diabetes status of the parents. To this end, association of mtDNA genetic backgrounds (haplogroups) with T2DM was assessed in 1055 Jewish patients with and without T2DM parents ('DP' and 'HP', respectively).
Haplogroup J1 was found to be 2.4 fold under-represented in the 'HP' patients (p = 0.0035). These results are consistent with a previous observation made in Finnish T2DM patients. Moreover, assessing the haplogroup distribution in 'DP' versus 'HP' patients having diabetic siblings revealed that haplogroup J1 was virtually absent in the 'HP' group.
These results imply the involvement of inherited factors, which modulate the susceptibility of haplogroup J1 to T2DM.
PMCID: PMC2706816  PMID: 19534826
5.  Common variants in WFS1 confer risk of type 2 diabetes 
Nature genetics  2007;39(8):951-953.
We studied genes involved in pancreatic β cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.
PMCID: PMC2672152  PMID: 17603484
6.  Post Genome-Wide Association Studies of Novel Genes Associated with Type 2 Diabetes Show Gene-Gene Interaction and High Predictive Value 
PLoS ONE  2008;3(5):e2031.
Recently, several Genome Wide Association (GWA) studies in populations of European descent have identified and validated novel single nucleotide polymorphisms (SNPs), highly associated with type 2 diabetes (T2D). Our aims were to validate these markers in other European and non-European populations, then to assess their combined effect in a large French study comparing T2D and normal glucose tolerant (NGT) individuals.
Methodology/Principal Findings
In the same French population analyzed in our previous GWA study (3,295 T2D and 3,595 NGT), strong associations with T2D were found for CDKAL1 (ORrs7756992 = 1.30[1.19–1.42], P = 2.3×10−9), CDKN2A/2B (ORrs10811661 = 0.74[0.66–0.82], P = 3.5×10−8) and more modestly for IGFBP2 (ORrs1470579 = 1.17[1.07–1.27], P = 0.0003) SNPs. These results were replicated in both Israeli Ashkenazi (577 T2D and 552 NGT) and Austrian (504 T2D and 753 NGT) populations (except for CDKAL1) but not in the Moroccan population (521 T2D and 423 NGT). In the overall group of French subjects (4,232 T2D and 4,595 NGT), IGFBP2 and CXCR4 synergistically interacted with (LOC38776, SLC30A8, HHEX) and (NGN3, CDKN2A/2B), respectively, encoding for proteins presumably regulating pancreatic endocrine cell development and function. The T2D risk increased strongly when risk alleles, including the previously discovered T2D-associated TCF7L2 rs7903146 SNP, were combined (8.68-fold for the 14% of French individuals carrying 18 to 30 risk alleles with an allelic OR of 1.24). With an area under the ROC curve of 0.86, only 15 novel loci were necessary to discriminate French individuals susceptible to develop T2D.
In addition to TCF7L2, SLC30A8 and HHEX, initially identified by the French GWA scan, CDKAL1, IGFBP2 and CDKN2A/2B strongly associate with T2D in French individuals, and mostly in populations of Central European descent but not in Moroccan subjects. Genes expressed in the pancreas interact together and their combined effect dramatically increases the risk for T2D, opening avenues for the development of genetic prediction tests.
PMCID: PMC2346547  PMID: 18461161
7.  Differences in mtDNA haplogroup distribution among 3 Jewish populations alter susceptibility to T2DM complications 
BMC Genomics  2008;9:198.
Recent genome-wide association studies searching for candidate susceptibility loci for common complex diseases such as type 2 diabetes mellitus (T2DM) and its common complications have uncovered novel disease-associated genes. Nevertheless these large-scale population screens often overlook the tremendous variation in the mitochondrial genome (mtDNA) and its involvement in complex disorders.
We have analyzed the mitochondrial DNA (mtDNA) genetic variability in Ashkenazi (Ash), Sephardic (Seph) and North African (NAF) Jewish populations (total n = 1179). Our analysis showed significant differences (p < 0.001) in the distribution of mtDNA genetic backgrounds (haplogroups) among the studied populations. To test whether these differences alter the pattern of disease susceptibility, we have screened our three Jewish populations for an association of mtDNA genetic haplogroups with T2DM complications. Our results identified population-specific susceptibility factors of which the best example is the Ashkenazi Jewish specific haplogroup N1b1, having an apparent protective effect against T2DM complications in Ash (p = 0.006), being absent in the NAF population and under-represented in the Seph population. We have generated and analyzed whole mtDNA sequences from the disease associated haplogroups revealing mutations in highly conserved positions that are good candidates to explain the phenotypic effect of these genetic backgrounds.
Our findings support the possibility that recent bottleneck events leading to over-representation of minor mtDNA alleles in specific genetic isolates, could result in population-specific susceptibility loci to complex disorders.
PMCID: PMC2386827  PMID: 18445251

Results 1-7 (7)