Affected Sibling Pairs Research Articles

Fine-mapping of prostate cancer aggressiveness loci on chromosome 7q22-35.

Deciphering the genetic basis of prostate cancer aggressiveness could provide valuable information for the screening and treatment of this common but complex disease. We previously detected linkage between a broad region on chromosome 7q22-35 and Gleason score-a strong predictor of prostate cancer aggressiveness. To further clarify this finding and focus on the potentially causative gene, we undertook a fine-mapping study across the 7q22-35 region. Our study population encompassed 698 siblings diagnosed with prostate cancer. 3,072 single nucleotide polymorphisms (SNPs) spanning the chromosome 7q22-35 region were genotyped using the Illumina GoldenGate assay. The impact of SNPs on Gleason scores were evaluated using affected sibling pair linkage and family-based association tests. We confirmed the previous linkage signal and narrowed the 7q22-35 prostate cancer aggressiveness locus to a 370 kb region. Centered under the linkage peak is the gene KLRG2 (killer cell lectin-like receptor subfamily G, member 2). Association tests indicated that the potentially functional non-synonymous SNP rs17160911 in KLRG2 was significantly associated with Gleason score (P = 0.0007). These findings suggest that genetic variants in the gene KLRG2 may affect Gleason score at diagnosis and hence the aggressiveness of prostate cancer.

A genomewide linkage study on suicidality in major depressive disorder confirms evidence for linkage to 2p12

Suicidal behavior is commonly associated with depression. Twin studies indicate that both suicidality and major depressive disorder (MDD) are heritable. However, epidemiological evidence suggests that the inheritance of suicidality is likely to be independent of the underlying psychiatric disorder, implying a distinct genetic contribution to suicidality. We conducted a genomewide linkage search aiming to detect genomic loci that may harbor susceptibility genes contributing to risk for suicidality in recurrent MDD. Affected sibling pair (ASP) variance components analysis was performed using the Depression Network cohort of 971 ASPs. The quantitative trait measuring suicidality as a broad phenotype, encompassing ideation and suicide attempts, was established from Schedules for Clinical Assessment in Neuropsychiatry interview items. We examined 1,060 genotyped microsatellite markers with an average spacing of 3.3 cM. Empirical thresholds for linkage evidence were set by whole-genome simulations (LOD = 2.71 for genomewide significance, 1.71 for suggestive linkage). No genomewide significant findings were found. Marker D3S1234 on 3p14 achieved suggestive linkage and yielded a maximum LOD of 1.853 (P = 0.0017), loci 9p24.3 and 18q22-q23 achieved LOD scores >1.5. We found some support for linkage to 2p12 (LOD = 1.2, P = 0.0087) which was previously implicated in linkage studies of suicidality. Our follow-up meta-analysis of five studies showed strong linkage to this region (P = 2 × 10(-6) ). In conclusion, this study analyzed suicidality as a continuous trait in MDD. We found modest evidence for linkage on 3p14. Our meta-analysis supports previous evidence of linkage to suicidality on 2p12. Some candidate genes in these regions may plausibly be implicated in suicidality. © 2010 Wiley-Liss, Inc.

Allele‐Sharing Statistics Using Information on Family History

When conducting genetic studies for complex traits, large samples are commonly required to detect new genetic factors. A possible strategy to decrease the sample size is to reduce heterogeneity using available information. In this paper we propose a new class of model-free linkage analysis statistics which takes into account the information given by the ungenotyped affected relatives (positive family history). This information is included into the scoring function of classical allele-sharing statistics. We studied pedigrees of affected sibling pairs with one ungenotyped affected relative. We show that, for rare allele common complex diseases, the proposed method increases the expected power to detect linkage. Allele-sharing methods were applied to the symptomatic osteoarthritis GARP study where taking into account the family-history increased considerably the evidence of linkage in the region of the DIO2 susceptibility locus.

Genetische Grundlagen der juvenilen idiopathischen Arthritis

Several genetic factors have recently been observed as having an influence on susceptibility, course and prognosis of juvenile idiopathic arthritis (JIA): 1. Affected sib pairs were observed to have a low concordance in terms of disease incidence, but significant concordance in terms of subtype and course of disease. 2. Each subtype of JIA was observed to have a distinct genetic background. 3. Some JIA patients do not carry any of the defined risk genes. 4. Most subtypes of JIA have a distinct different genetic background to rheumatoid arthritis in adults. 5. Multiple factors have been observed to be involved in pathogenesis implying genetic and environmental factors. 6. Systemic JIA differs from all other subtypes in terms of genetic background and treatment options. It is currently assumed to be an autoinflammatory disease. 7. Genetic factors not only affect the course of the disease, but also response and complication rate. Increasing knowledge on the factors involved in the pathogenesis of JIA as well as analysis of large patient cohorts in consortiums cooperating on an international level have helped define many important polymorphisms; these are currently the subject of further investigation.

Evidence for linkage of the bladder exstrophy‐epispadias complex on chromosome 4q31.21‐22 and 19q13.31‐41 from a consanguineous iranian family

The bladder exstrophy-epispadias complex (BEEC) is a spectrum of anomalies involving the abdominal wall, pelvis, urinary tract, genitalia, and, occasionally, the spine and anus. Although BEEC typically occurs sporadically, families with two or more affected members have been reported. The present authors previously conducted a genome-wide linkage analysis in two multiply affected (multiplex) families (one of German and one of Spanish origin), which revealed several chromosomal regions compatible with linkage. In the present study, genome-wide linkage analysis was performed in a recently reported consanguineous Iranian multiplex family with an affected sibling pair: a female with epispadias and a male with classic exstrophy of the bladder. The Affymetrix 250K Sty chip (238,304 single nucleotide polymorphisms) was used to genotype the parents and four children, including the two affected siblings. Parametric and nonparametric linkage analyses were performed. Parametric linkage analysis under a recessive model with complete penetrance identified seven loci with LOD scores >1.6 (1p33, 4q31.21-22, 9q22.33, 12q13.13-2, 13q12.12-13, 18q23, and 19q13.31-41). These results were supported by nonparametric linkage analysis. Haplotype analysis showed that the affected individuals were homozygous identical by descent for all seven regions. Two of these regions overlapped with regions observed previously in the Spanish family -one on chromosome 4q31.21-22, and the other on chromosome 19q13.31-41. These results suggest that chromosomal regions 4q31.21-22 and 19q13.31-41 are likely to harbor genes for an autosomal recessive form of BEEC.

Designing and implementing sample and data collection for an international genetics study: the Type 1 Diabetes Genetics Consortium (T1DGC).

Background and Purpose The Type 1 Diabetes Genetics Consortium (T1DGC) is an international project whose primary aims are to: (a) discover genes that modify type 1 diabetes risk; and (b) expand upon the existing genetic resources for type 1 diabetes research. The initial goal was to collect 2500 affected sibling pair (ASP) families worldwide.Methods T1DGC was organized into four regional networks (Asia-Pacific, Europe, North America, and the United Kingdom) and a Coordinating Center. A Steering Committee, with representatives from each network, the Coordinating Center, and the funding organizations, was responsible for T1DGC operations. The Coordinating Center, with regional network representatives, developed study documents and data systems. Each network established laboratories for: DNA extraction and cell line production; human leukocyte antigen genotyping; and autoantibody measurement. Samples were tracked from the point of collection, processed at network laboratories and stored for deposit at National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories. Phenotypic data were collected and entered into the study database maintained by the Coordinating Center.Results T1DGC achieved its original ASP recruitment goal. In response to research design changes, the T1DGC infrastructure also recruited trios, cases, and controls. Results of genetic analyses have identified many novel regions that affect susceptibility to type 1 diabetes. T1DGC created a resource of data and samples that is accessible to the research community.Limitations Participation in T1DGC was declined by some countries due to study requirements for the processing of samples at network laboratories and/or final deposition of samples in NIDDK Central Repositories. Re-contact of participants was not included in informed consent templates, preventing collection of additional samples for functional studies.Conclusions T1DGC implemented a distributed, regional network structure to reach ASP recruitment targets. The infrastructure proved robust and flexible enough to accommodate additional recruitment. T1DGC has established significant resources that provide a basis for future discovery in the study of type 1 diabetes genetics.

HLA genotyping in the international Type 1 Diabetes Genetics Consortium

Background Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers.Purpose In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years.Methods Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences.Results A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances.Limitations The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required.Conclusions High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies.

Genome-Wide Association Study of Major Recurrent Depression in the U.K. Population

Studies of major depression in twins and families have shown moderate to high heritability, but extensive molecular studies have failed to identify susceptibility genes convincingly. To detect genetic variants contributing to major depression, the authors performed a genome-wide association study using 1,636 cases of depression ascertained in the U.K. and 1,594 comparison subjects screened negative for psychiatric disorders. Cases were collected from 1) a case-control study of recurrent depression (the Depression Case Control [DeCC] study; N=1346), 2) an affected sibling pair linkage study of recurrent depression (probands from the Depression Network [DeNT] study; N=332), and 3) a pharmacogenetic study (the Genome-Based Therapeutic Drugs for Depression [GENDEP] study; N=88). Depression cases and comparison subjects were genotyped at Centre National de Génotypage on the Illumina Human610-Quad BeadChip. After applying stringent quality control criteria for missing genotypes, departure from Hardy-Weinberg equilibrium, and low minor allele frequency, the authors tested for association to depression using logistic regression, correcting for population ancestry. Single nucleotide polymorphisms (SNPs) in BICC1 achieved suggestive evidence for association, which strengthened after imputation of ungenotyped markers, and in analysis of female depression cases. A meta-analysis of U.K. data with previously published results from studies in Munich and Lausanne showed some evidence for association near neuroligin 1 (NLGN1) on chromosome 3, but did not support findings at BICC1. This study identifies several signals for association worthy of further investigation but, as in previous genome-wide studies, suggests that individual gene contributions to depression are likely to have only minor effects, and very large pooled analyses will be required to identify them.

Genetics of longevity

Epidemiological and family-based studies in different populations underlined the existence of a genetic component in human longevity. Studies on families of centenarians demonstrated that parents, siblings and offspring of long-lived subjects have a significant survival advantage. In particular, the survival curve of siblings of centenarians is significantly higher than that people belonging to the same birth cohort. Moreover, siblings of centenarians have a lower risk of suffering from major age-related diseases, such as cardiovascular diseases, diabetes and cancer, when compared to appropriate selected controls from the same population. Indeed, studies on the concordance of the age of death in twins demonstrated a higher correlation in monozygotic than dyzigotic twins and suggested that approximately 25% of the variation in adult lifespan is caused by genetic differences between individuals. It was also demonstrated that the genetic component affecting longevity increases at advanced ages and it is generally stronger in males than in females. Furthermore, a positive correlation between population homozygosity and longevity was suggested, confirming the relevance of genetic differences between individuals for the susceptibility to a long lifespan. Identifying genes that affect human longevity can provide information about the molecular mechanisms involved in the aging process and shed light on the heterogeneity of the aging phenotype. Studies on experimental models suggest that caloric restriction improves age-related health and slow the aging process by limiting energy intake. Furthermore, in animal models specific alterations in single genes (age-1, daf2, sir2, methusela, p66) can dramatically extend or decrease lifespan. In humans, evidence is accumulating for an additive multilocus model, i.e. multiple genes with modest effect, working independently and as a network [1]. Because of the suggested additive effects of different genetic variants predisposing to longevity, the combined approach of linkage analysis in affected sib pairs (ASP) in candidate regions for high frequent variants and Genome Wide Association for less frequent polymorphisms [1] is considered promising for the identification of the genetic component of human longevity. Among the genes for which association has been demonstrated with human longevity, there are Apolipoprotein genes (APOE, APOB, ACE, APOC3), sirtuin genes (SIRT1 and SIRT3), genes belonging to the anti-oxidant (SOD1, SOD2, PON1, FOXO3A) and inflammatory pathways (Klotho, CETP, IL6). A relevant role seems to be represented also by the inherited and somatic variability of the mitochondrial genome.

Characterization of a Family with Rare Deletions in CNTNAP5 and DOCK4 Suggests Novel Risk Loci for Autism and Dyslexia

BackgroundAutism spectrum disorders (ASDs) are characterized by social, communication, and behavioral deficits and complex genetic etiology. A recent study of 517 ASD families implicated DOCK4 by single nucleotide polymorphism (SNP) association and a microdeletion in an affected sibling pair.MethodsThe DOCK4 microdeletion on 7q31.1 was further characterized in this family using QuantiSNP analysis of 1M SNP array data and reverse transcription polymerase chain reaction. Extended family members were tested by polymerase chain reaction amplification of junction fragments. DOCK4 dosage was measured in additional samples using SNP arrays. Since QuantiSNP analysis identified a novel CNTNAP5 microdeletion in the same affected sibling pair, this gene was sequenced in 143 additional ASD families. Further polymerase chain reaction-restriction fragment length polymorphism analysis included 380 ASD cases and suitable control subjects.ResultsThe maternally inherited microdeletion encompassed chr7:110,663,978-111,257,682 and led to a DOCK4-IMMP2L fusion transcript. It was also detected in five extended family members with no ASD. However, six of nine individuals with this microdeletion had poor reading ability, which prompted us to screen 606 other dyslexia cases. This led to the identification of a second DOCK4 microdeletion co-segregating with dyslexia. Assessment of genomic background in the original ASD family detected a paternal 2q14.3 microdeletion disrupting CNTNAP5 that was also transmitted to both affected siblings. Analysis of other ASD cohorts revealed four additional rare missense changes in CNTNAP5. No exonic deletions of DOCK4 or CNTNAP5 were seen in 2091 control subjects.ConclusionsThis study highlights two new risk factors for ASD and dyslexia and demonstrates the importance of performing a high-resolution assessment of genomic background, even after detection of a rare and likely damaging microdeletion using a targeted approach.

A systematic gene-based screen of chr4q22–q32 identifies association of a novel susceptibility gene, DKK2 , with the quantitative trait of alcohol dependence symptom counts

Studies of alcohol dependence (AD) have consistently found evidence of linkage on chromosome 4q21-q32. A genome-wide linkage scan in the Irish Affected Sib Pair Study of Alcohol Dependence (IASPSAD) sample also provided its strongest evidence of linkage on chromosome 4q22-q32 using an index of AD severity based on the count of DSM-IV AD symptoms (ADSX; LOD = 4.59). We conducted a systematic, gene-centric association study using 518 LD-tagging single nucleotide polymorphisms (SNPs) in the 65 known and predicted genes within the 1-LOD interval surrounding the linkage peak. Case-only regression analysis with the quantitative variable of ADSX was performed in the 562 genetically independent cases; nominal support for association was demonstrated by 32 tagging SNPs in 14 genes. We did not observe study-wide significance, but gene-wise correction for multiple testing with the Nyholt procedure yielded empirical evidence of association with two genes, DKK2 (dickkopf homolog 2) (P = 0.007) and EGF (epidermal growth factor) (P = 0.025) in the IASPSAD sample. Three SNPs in DKK2 (rs427983; rs419558; rs399087) demonstrated empirical significance. Assessment of possible replication in 847 cases of European descent from a large independent sample, the Collaborative Study of the Genetics of Alcoholism, yielded replication for DKK2 but not EGF. We observed genotypic and phenotypic replication for DKK2 with the three SNPs yielding significant association with ADSX in the IASPSAD sample. Haplotype-specific expression measurements in post-mortem tissue samples suggested a functional role for DKK2. This evidence notwithstanding, replication is needed before confidence can be placed in these findings.

Supervised machine learning and logistic regression identifies novel epistatic risk factors with PTPN22 for rheumatoid arthritis

Investigating genetic interactions (epistasis) has proven difficult despite the recent advances of both laboratory methods and statistical developments. With no 'best' statistical approach available, combining several analytical methods may be optimal for detecting epistatic interactions. Using a multi-stage analysis that incorporated supervised machine learning and methods of association testing, we investigated epistatic interactions with a well-established genetic factor (PTPN22 1858T) in a complex autoimmune disease (rheumatoid arthritis (RA)). Our analysis consisted of four principal stages: Stage I (data reduction)-identifying candidate chromosomal regions in 292 affected sibling pairs, by predicting PTPN22 concordance using multipoint identity-by-descent probabilities and a supervised machine learning algorithm (Random Forests); Stage II (extension analysis)-testing detailed genetic data within candidate chromosomal regions for epistasis with PTPN22 1858T in 677 cases and 750 controls using logistic regression; Stage III (replication analysis)-confirmation of epistatic interactions in 947 cases and 1756 controls; Stage IV (combined analysis)-a pooled analysis including all 1624 RA cases and 2506 control subjects for final estimates of effect size. A total of seven replicating epistatic interactions were identified. SNP variants within CDH13, MYO3A, CEP72 and near WFDC1 showed significant evidence for interaction with PTPN22, affecting susceptibility to RA.

Identification of KCNJ15 as a Susceptibility Gene in Asian Patients with Type 2 Diabetes Mellitus

Recent advances in genome research have enabled the identification of new genomic variations that are associated with type 2 diabetes mellitus (T2DM). Via fine mapping of SNPs in a candidate region of chromosome 21q, the current study identifies potassium inwardly-rectifying channel, subfamily J, member 15 (KCNJ15) as a new T2DM susceptibility gene. KCNJ15 is expressed in the beta cell of the pancreas, and a synonymous SNP, rs3746876, in exon 4 (C566T) of this gene, with T allele frequency among control subjects of 3.1%, showed a significant association with T2DM affecting lean individuals in three independent Japanese sample sets (p = 2.5 x 10(-7), odds ratio [OR] = 2.54, 95% confidence interval [CI] = 1.76-3.67) and with unstratified T2DM (p = 6.7 x 10(-6), OR = 1.76, 95% CI = 1.37-2.25). The diabetes risk allele frequency was, however, very low among Europeans in whom no association between this variant and T2DM could be shown. Functional analysis in human embryonic kidney 293 cells demonstrated that the risk allele of the synonymous SNP in exon 4 increased KCNJ15 expression via increased mRNA stability, which resulted in the higher expression of protein as compared to that of the nonrisk allele. We also showed that KCNJ15 is expressed in human pancreatic beta cells. In conclusion, we demonstrated a significant association between a synonymous variant in KCNJ15 and T2DM in lean Japanese patients with T2DM, suggesting that KCNJ15 is a previously unreported susceptibility gene for T2DM among Asians.

Linkage and Association Studies of Joint Morbidity from Rheumatoid Arthritis

To investigate the relationship between genetic variations of rheumatoid arthritis (RA) susceptibility in terms of joint morbidity. We used data from Genetic Analysis Workshop 15. The Illumina linkage panel IV included 5858 single-nucleotide polymorphisms (SNP), with 5744 SNP passing quality control filters. The phenotypic variables analyzed were the level of rheumatoid factor (RF) and score on the Joint Alignment and Motion (JAM) scale. We modified the scale, dividing by RF values relevant to disease severity. Linkage analysis for affected sibling pairs was done using the MERLIN program, and family-based association tests were carried out using PLINK and FBAT software. We found a high peak (LOD = 3.29; NPL Z = 4.07) near the HLA-DRB1 region on chromosome 6. The linkage at 6p24 at rs1410766 [LOD = 2.66; nonparametric linkage (NPL) Z = 3.23] was statistically significant. Two other regions also showed possible linkage peaks: chromosome 7q30 at rs322812 (LOD = 2.47; NPL Z = 3.39) and chromosome 15p34 at rs347117 (LOD = 1.95; NPL Z = 2.80). For the family-based association study, 7 SNP related to clinical RA severity were detected. Genetic variations may lead to an enhanced risk of joint damage and increased levels of RF. Further studies are needed to elucidate the roles of other genes involved in RA and to explore whether the clinical signs of RA are associated with particular genetic variations.

Familiality and molecular genetics of attention networks in ADHD

Indices from a more elementary neuropsychological level might be useful in the search for genes for complex psychiatric disorders, such as ADHD. In this study we investigated systematically whether attentional performance as measured with the Attention Network Test (ANT) is suited for the identification of endophenotypes of ADHD. Attentional performance in affected sib pairs with ADHD (n = 181) was compared to unaffected control siblings (n = 121). Intrafamilial correlation patterns were calculated. In addition, linkage and association analyses were conducted between quantitative scores of attentional functions and dopamine receptor D4 (DRD4) and dopamine transporter (DAT1 or SLC6A3) gene variants. Only the executive attention network was significantly impaired in subjects with ADHD compared to controls (P < 0.05) and showed evidence for familiality in both affected and unaffected families. Linkage analyses revealed the highest LOD score for a severity score based on DSM-IV inattentive symptoms in the DAT1 chromosomal region (LOD score 2.6 at 15 cM). However, a SNP (rs6350) at the DAT1 locus showed a tendency for association with both alerting performance (P = 0.02) and executive attention (P = 0.01) although it did not survive alpha adjustment for multiple testing. No evidence was found for association of any of the investigated phenotypes with the VNTR in the DRD4. Thus, our data suggest that the quantitative behavioral ratings of inattentive symptoms might be more useful when searching for new genes associated with ADHD, however, among the ANT measures the executive attention network seems to be best suited for further endophenotype analyses.

Empirically defined subtypes of alcohol dependence in an Irish family sample

Alcohol dependence (AD) is clinically and etiologically heterogeneous. The goal of this study was to explore AD subtypes among a sample of 1221 participants in the Irish Affected Sib Pair Study of Alcohol Dependence, all of whom met DSM-IV criteria for AD. Variables used to identify the subtypes included major depressive disorder, antisocial personality disorder, illicit drug dependence (cannabis, sedatives, stimulants, cocaine, opioids, and hallucinogens), nicotine dependence, the personality traits of neuroticism and novelty seeking, and early alcohol use. Using latent class analysis, a 3-class solution was identified as the most parsimonious description of the data. Individuals in a Mild class were least likely to have comorbid psychopathology, whereas a severe class had highest probabilities of all comorbid psychopathology. The third class was characterized by high probabilities of major depression and higher neuroticism scores, but lower likelihood of other comorbid disorders than seen in the severe class. Overall, sibling pair resemblance for class was stronger within than between classes, and was greatest for siblings within the severe class, suggesting a stronger familial etiology for this class. These findings are consistent with the affective regulation and behavioral disinhibition subtypes of alcoholism, and are in line with prior work suggesting familial influences on subtype etiology.

The type I diabetes association of the IL2RA locus

To confirm and fine map previous reports of association, the Type I Diabetes (T1D) Genetics Consortium (T1DGC) assembled a large collection of DNA samples from affected sib-pair (ASP) families with T1D (5003 affected individuals) and genotyped polymorphic markers. One of these loci, involving the IL2RA gene, had been reported to be due to three independent effects. The T1DGC genotyped 69 single-nucleotide polymorphisms (SNPs) that span approximately 88 kb from the 5' flanking to 3' flanking region of the IL2RA locus. The most highly associated SNP reported earlier (ss52580101) was not included in the genotyping list; however, a 5-SNP (rs3134883, rs3118470, rs7072793, rs4749955 and rs12251307) haplotype (H5) was identified that strongly tagged its minor allele with r(2)=0.869 (95% CI, 0.850-0.885). This haplotype was significantly protective (P=3.2 x 10(-5)) in the T1D ASP families, with an odds ratio virtually identical to that reported for ss52580101. The SNP marking the second independent locus, (rs11594656) showed no association in the T1DGC set and the third (rs2104286) could not be distinguished, by conditional regression, from H5. Instead, the most significant independent effect was detected from the 5' flanking IL2RA SNP rs4749955, which remained significant after regression for H5. Thus, we confirm independent effects at the IL2RA locus.

Rs2476601 T allele (R620W) defines high-risk PTPN22 type I diabetes-associated haplotypes with preliminary evidence for an additional protective haplotype

Protein tyrosine phosphatase non-receptor type 22 (PTPN22) is the third major locus affecting risk of type I diabetes (T1D), after HLA-DR/DQ and INS. The most associated single-nucleotide polymorphism (SNP), rs2476601, has a C->T variant and results in an arginine (R) to tryptophan (W) amino acid change at position 620. To assess whether this, or other specific variants, are responsible for T1D risk, the Type I Diabetes Genetics Consortium analyzed 28 PTPN22 SNPs in 2295 affected sib-pair (ASP) families. Transmission Disequilibrium Test analyses of haplotypes revealed that all three haplotypes with a T allele at rs2476601 were overtransmitted to affected children, and two of these three haplotypes showed statistically significant overtransmission (P=0.003 to P=5.9E-12). Another haplotype had decreased transmission to affected children (P=3.5E-05). All haplotypes containing the rs2476601 T allele were identical for all SNPs across PTPN22 and only varied at centromeric SNPs. When considering rs2476601 'C' founder chromosomes, a second haplotype (AGGGGC) centromeric of PTPN22 in the C1orf178 region was associated with protection from T1D (odds ratio=0.81, P=0.0005). This novel finding requires replication in independent populations. We conclude the major association of PTPN22 with T1D is likely due to the recognized non-synonymous SNP rs2476601 (R620W).

Overview of the Rapid Response data.

The Type I Diabetes Genetics Consortium (T1DGC) Rapid Response Workshop was established to evaluate published candidate gene associations in a large collection of affected sib-pair (ASP) families. We report on our quality control (QC) and preliminary family-based association analyses. A random sample of blind duplicates was analyzed for QC. Quality checks, including examination of plate-panel yield, marker yield, Hardy-Weinberg equilibrium, mismatch error rate, Mendelian error rate, and allele distribution across plates, were performed. Genotypes from 2324 families within nine cohorts were obtained from a panel of 21 candidate genes, including 384 single-nucleotide polymorphisms on two genotyping platforms performed at the Broad Institute Center for Genotyping and Analysis (Cambridge, MA, USA). The T1DGC Rapid Response project, following rigorous QC procedures, resulted in a 2297 family, 9688 genotyped individual database on a single-candidate gene panel. The available data include 9005 individuals with genotype data from both platforms and 683 individuals genotyped (276 in Illumina; 407 in Sequenom) on only one platform.

Use of supplementary phenotype to identify additional rheumatoid arthritis loci in a linkage analysis of 342 UK affected sibling pair families

BackgroundAlthough rheumatoid arthritis has been shown to have moderately strong genetic component, both linked loci identified in linkage analyses and susceptibility variants from association studies are short of adequately accounting for a comprehensive catalogue of the molecular factors underlying this complex disease. The objective of this study was to use supplementary phenotype based on cumulative hazard of rheumatoid arthritis to identify linkage evidence for new and additional rheumatoid arthritis loci in a genome-wide linkage analysis of 342 affected sibling pair families from the United Kingdom.MethodsUsing proportional hazards model, we estimated cumulative hazard of rheumatoid arthritis and then used it as a quantitative trait in a non-parametric multipoint variance component linkage analysis with 353 microsatellite markers distributed across the 22 autosomal chromosomes.ResultsWe identified 3 new loci with genome-wide suggestive linkage evidence for rheumatoid arthritis on 9q21.13, 15p11.1 and 20q13.33. Our results also confirmed previously reported linkage evidence in the HLA-DRB1 region on chromosome 6 and on locus 1q32.1.ConclusionThis study demonstrates the potential for information gain through the use of supplementary phenotypes in genetic study of complex diseases to identify new and additional potential linked loci that are not detected by linkage analysis of traditional phenotypes; and our results provide further evidence of the involvement of multiple loci in the genetic aetiology of rheumatoid arthritis.