The Transmission Disequilibrium Test (TDT) is a family-based test for association based on the rate of transmission of alleles from heterozygous parents to affected offspring, and has gained ...popularity as this test preserves the Type I error rate. Population stratification results in a decreased number of heterozygous parents compared to that expected assuming Hardy-Weinberg Equilibrium (Wahlund Effect). We show that population stratification changes the relative proportion of the informative mating types. The decrease in the number of heterozygous parents and the change in the relative proportion of the informative mating types result in significant changes to the sample sizes required to achieve the power desired. We show examples of the changes in sample sizes, and provide an easy method for estimating TDT sample sizes in the presence of population stratification. This method potentially aids in reducing the number of false-negative association studies.
A Genome-Wide Linkage Scan for Genes Controlling Variation in Renal Function Estimated by Serum Cystatin C Levels in Extended
Families With Type 2 Diabetes
Grzegorz Placha 1 2 3 ,
G. David Poznik 1 ,
...Jonathon Dunn 1 ,
Adam Smiles 1 ,
Bozena Krolewski 1 2 ,
Timothy Glew 1 ,
Sobha Puppala 4 ,
Jennifer Schneider 4 ,
John J. Rogus 1 2 ,
Stephen S. Rich 5 ,
Ravindranath Duggirala 4 ,
James H. Warram 1 and
Andrzej S. Krolewski 1 2
1 Research Division, Joslin Diabetes Center, Boston, Massachusetts
2 Department of Medicine, Harvard Medical School, Boston, Massachusetts
3 Department of Internal Medicine and Hypertension, Warsaw Medical University, Warsaw, Poland
4 Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas
5 Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
Address correspondence and reprint requests to Andrzej S. Krolewski, MD, PhD, Section on Genetics and Epidemiology, Joslin
Diabetes Center, One Joslin Place, Boston, MA 02215. E-mail: andrzej.krolewski{at}joslin.harvard.edu
Abstract
We performed a variance components linkage analysis of renal function, measured as glomerular filtration rate (GFR), in 63
extended families with multiple members with type 2 diabetes. GFR was estimated from serum concentrations of cystatin C and
creatinine in 406 diabetic and 428 nondiabetic relatives. Results for cystatin C were summarized because they are superior
to creatinine results. GFR aggregates in families with significant heritability ( h 2 ) in diabetic ( h 2 = 0.45, P < 1 × 10 −5 ) and nondiabetic ( h 2 = 0.36, P < 1 × 10 −3 ) relatives. Genetic correlation ( r G = 0.35) between the GFR of diabetic and nondiabetic relatives was less than one ( P = 0.01), suggesting that genes controlling GFR variation in these groups are different. Linkage results supported this interpretation.
In diabetic relatives, linkage was strong on chromosome 2q (logarithm of odds LOD = 4.1) and suggestive on 10q (LOD = 3.1)
and 18p (LOD = 2.2). In nondiabetic relatives, linkage was suggestive on 3q (LOD = 2.2) and 11p (LOD = 2.1). When diabetic
and nondiabetic relatives were combined, strong evidence for linkage was found only on 7p (LOD = 4.0). In conclusion, partially
distinct sets of genes control GFR variation in relatives with and without diabetes on chromosome 2q, possibly on 10q and
18p in the former, and on 7p in both. None of these genes overlaps with genes controlling variation in urinary albumin excretion.
ACR, albumin-to-creatinine ratio
CC-GFR, GFR estimated by cystatin C measured in micrograms per liter multiplied by 100
CG-GFR, Cockcroft-Gault estimate of GFR
ESRD, end-stage renal disease
G × DM, genotype by diabetes
GFR, glomerular filtration rate
LOD, logarithm of odds
logACR, ACR values transformed to a base 10 logarithm and multiplied by 10
MDRD, Modification of Diet in Renal Disease
MDRD-GFR, MDRD estimate of GFR
QTLs, quantitative trait loci
Footnotes
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore
be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Accepted September 6, 2006.
Received June 7, 2006.
DIABETES
The Genetics of Kidneys in Diabetes (GoKinD) study is an initiative that aims to identify genes that are involved in diabetic nephropathy. A large number of individuals with type 1 diabetes were ...screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents also were enrolled to form family trios. As of November 2005, GoKinD included 3075 participants who comprise 671 case singletons, 623 control singletons, 272 case trios, and 323 control trios. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form that are available at http://www.gokind.org/access. Participating scientists will have access to three data sets, each with distinct advantages. The set of 1294 singletons has adequate power to detect a wide range of genetic effects, even those of modest size. The set of case trios, which has adequate power to detect effects of moderate size, is not susceptible to false-positive results because of population substructure. The set of control trios is critical for excluding certain false-positive results that can occur in case trios and may be particularly useful for testing gene-environment interactions. Integration of the evidence from these three components into a single, unified analysis presents a challenge. This overview of the GoKinD study examines in detail the power of each study component and discusses analytic challenges that investigators will face in using this resource.
Epidemiological and family studies have demonstrated that susceptibility genes play an important role in the etiology of diabetic nephropathy, defined as persistent proteinuria or end-stage renal ...disease (ESRD) in type 1 diabetes.
To efficiently search for genomic regions harboring diabetic nephropathy genes, we conducted a scan using 5,382 informative single nucleotide polymorphisms on 100 sibpairs concordant for type 1 diabetes but discordant for diabetic nephropathy. In addition to being powerful for detecting linkage to diabetic nephropathy, this design allows linkage analysis on type 1 diabetes via traditional affected sibpair (ASP) analysis. In weighing the evidence for linkage, we considered maximum logarithm of odds score (maximum likelihood score MLS) values and corresponding allelic sharing patterns, calculated and viewed graphically using the software package SPLAT.
Our primary finding for diabetic nephropathy, broadly defined, is on chromosome 19q (MLS = 3.1), and a secondary peak exists on chromosome 2q (MLS = 2.1). Stratification of discordant sibpairs based on whether disease had progressed to ESRD suggested four tertiary peaks on chromosome 1q (ESRD only), chromosome 20p (proteinuria only), and chromosome 3q (two loci 58 cm apart, one for ESRD only and another for proteinuria only). Additionally, analysis of 130 ASPs for type 1 diabetes confirmed the linkage to the HLA region on chromosome 6p (MLS = 9.2) and IDDM15 on chromosome 6q (MLS = 3.1).
This study identified several novel loci as candidates for diabetic nephropathy, none of which appear to be the sole genetic determinant of diabetic nephropathy in type 1 diabetes. In addition, this study confirms two previously reported type 1 diabetes loci.
Polymorphism in Ecto-Nucleotide Pyrophosphatase/Phosphodiesterase 1 Gene ( ENPP1/PC-1 ) and Early Development of Advanced Diabetic Nephropathy in Type 1 Diabetes
Luis H. Canani ,
Daniel P.K. Ng ,
...Adam Smiles ,
John J. Rogus ,
James H. Warram and
Andrzej S. Krolewski
From the Research Division, Joslin Diabetes Center, and the Department of Medicine, Harvard Medical School, Boston, Massachusetts
Abstract
A polymorphism in the ecto-nucleotide pyrophosphatase/phosphodiesterase 1 gene ( ENPP1 ) (previously known as PC-1 ), resulting in an amino acid change from lysine to glutamine at codon 121 (K121Q), is associated with insulin resistance.
A small follow-up study of patients with type 1 diabetes and proteinuria found that renal function declines more rapidly in
carriers of the Q variant than in noncarriers. To examine this finding further, we conducted a large case-control study and
a family-based study. Genomic DNA was obtained from 659 patients: 307 with normal urinary albumin excretion despite diabetes
duration of >15 years (control subjects) and 352 with advanced diabetic nephropathy, of whom 200 had persistent proteinuria
and 152 had end-stage renal disease (ESRD). Individuals were genotyped for Q and K variants using a previously described protocol.
The frequency of Q variant carriers was 21.5% in control subjects, 31.5% in subjects with proteinuria, and 32.2% in subjects
with ESRD ( P = 0.012). In a stratified analysis according to duration of diabetes, the risk of early-onset ESRD for carriers of the Q
variant was 2.3 times that for noncarriers (95% CI, 1.2–4.6). The Q variant was not associated with late-onset ESRD. Similar
findings were obtained in a family-based study. We conclude that carriers of the Q variant of ENPP1 are at increased risk for developing ESRD early in the course of type 1 diabetes.
Footnotes
Address correspondence and reprint requests to Andrzej S. Krolewski, Section on Genetics and Epidemiology, Research Division,
Joslin Diabetes Center, One Joslin Place, Boston, MA 02215. E-mail: andrzej.krolewski{at}joslin.harvard.edu .
Received for publication 31 July 2001 and accepted in revised form 4 January 2002.
ACR, albumin/creatinine ratio; ESRD, end-stage renal disease; GFR, glomerular filtration rate; IRS, insulin receptor substrate;
TDT, transmission disequilibrium test.
DIABETES
Summary
Identifying population stratification and genotyping error are important for candidate gene association studies using the Transmission Disequilibrium Test (TDT). Although the TDT retains the ...prespecified Type I error in the presence of population stratification, the test may have decreased power in the presence of population stratification. Genotyping error can also cause the TDT to have an elevated Type I error. Differentiating population stratification from genotyping error remains a challenge for geneticists. Both genotyping error and population stratification can result in an increase in the observed homozygosity of a sample relative to that expected assuming Hardy‐Weinberg Equilibrium (HWE). We show that when family data are available, even if a limited number of markers are genotyped, evaluating the markers that show statistically significant deviation from HWE with the Mating Type Distortion Test (MTDT) – a test based on the mating type distribution – can reliably differentiate genotyping error from population stratification. We simulate data based on several models of genotyping error in previously published literature, and show how this method could be used in practice to assist in differentiating population stratification from systematic genotyping error.
Diabetic nephropathy (DN) clusters in families with type 1 diabetes and the degree of clustering suggests that a major gene having a common disease allele may be responsible. To investigate the ...chromosomal regions containing genes for the renin-angiotensin system, we performed a linkage study using pairs of siblings with type 1 diabetes who were discordant for DN. Theoretical considerations supported by simulation studies indicated that such discordant pairs, rather than the usual concordant pairs, would be more effective in detecting a major susceptibility gene for DN. We applied this novel strategy to test for linkage between DN and chromosomal regions containing genes for the ACE, angiotensinogen (AGT), and angiotensin II type 1 receptor (AT1). Two polymorphic markers were genotyped in the vicinity of each of the three loci in 66 discordant sib pairs and were analyzed with multipoint methods. The regions containing ACE and AGT loci were not linked with DN, while the region containing the AT1 locus showed linkage with DN. As a result of these positive findings, eight additional polymorphic markers spanning a 63-cM region around AT1 locus were genotyped. Linkage was demonstrated between DN and a 20-cM region that includes AT1 (P = 7.7 x 10(-5)), an obvious candidate gene for DN. To investigate whether AT1 could account for the observed linkage, we sequenced all exons, splicing junctions, and the promoter region and examined the identified polymorphisms/mutations for association with DN using the transmission disequilibrium test. Four new polymorphisms in the gene were found, but neither these nor previously described polymorphisms were associated with DN. Thus, while our study does not implicate AT1 itself in the etiology of DN, it provides very strong evidence that a 20-cM region around AT1 contains a major locus for susceptibility to DN.
Genes play a role in many processes underlying late diabetic complications, but efforts to identify genetic variants have produced disappointing and contradictory results. Here, we evaluate whether ...the study designs and analytic methods commonly being used are optimal for finding susceptibility genes for diabetic complications. We do so by generating plausible genetic models and assessing the performance of case-control and family-based trio study designs. What emerges as a key determinant of success is duration of diabetes. This perspective focuses on duration of diabetes before complication onset and its influence on the ability to detect major and minor gene effects. It does not delve into the distinct effect of duration after complication onset, which can enrich case subjects with genotypes conferring survival advantage. We use clinically diagnosed nephropathy in type 1 diabetes to show how ignoring duration can result in considerable power loss in both case-control and family-based trio designs. We further show how, under certain circumstances, disregard for duration information can paradoxically lead to implicating nonrisk alleles as causative. Our results indicate that problems can be minimized by selecting case subjects with short diabetes duration and, to a lesser extent, control subjects with long duration or, perhaps, by adjusting for duration during analysis.
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