Concordance for clonal hematopoiesis is limited in elderly twins.

Although acquisition of leukemia-associated somatic mutations by 1 or more hematopoietic stem cells is inevitable with advancing age, its consequences are highly variable, ranging from clinically silent clonal hematopoiesis (CH) to leukemic progression. To investigate the influence of heritable factors on CH, we performed deep targeted sequencing of blood DNA from 52 monozygotic (MZ) and 27 dizygotic (DZ) twin pairs (aged 70-99 years). Using this highly sensitive approach, we identified CH (variant allele frequency ≥0.5%) in 62% of individuals. We did not observe higher concordance for CH within MZ twin pairs as compared with that within DZ twin pairs, or to that expected by chance. However, we did identify 2 MZ pairs in which both twins harbored identical rare somatic mutations, suggesting a shared cell of origin. Finally, in 3 MZ twin pairs harboring mutations in the same driver genes, serial blood samples taken 4 to 5 years apart showed substantial twin-to-twin variability in clonal trajectories. Our findings propose that the inherited genome does not exert a dominant influence on the behavior of adult CH and provide evidence that CH mutations may be acquired in utero.

Genome-wide survey of copy number variants finds MAPT duplications in progressive supranuclear palsy.

BACKGROUND: Progressive supranuclear palsy is a neurodegenerative tauopathy manifesting clinically as a progressive akinetic-rigid syndrome. In this study, we sought to identify genetic variants influencing PSP susceptibility through a genome-wide association analysis of a cohort of well-characterized patients who had participated in the Neuroprotection and Natural History in Parkinson Plus Syndromes and Blood Brain Barrier in Parkinson Plus Syndromes studies. METHODS: We genotyped single-nucleotide polymorphisms in 283 PSP cases from the United Kingdom, Germany, and France and compared these with genotypes from 4472 controls. Copy number variants were identified from genotyping data. RESULTS: We observed associations on chromosome 17 within or close to the MAPT gene and explored the genetic architecture at this locus. We confirmed the previously reported association of rs1768208 in the MOBP gene (P = 3.29 × 10-13 ) and rs1411478 in STX6 (P = 3.45 × 10-10 ). The population-attributable risk from the MAPT, MOBP, and STX6 single-nucleotide polymorphisms was found to be 0.37, 0.26, and 0.08, respectively. In addition, we found 2 instances of copy number variants spanning the MAPT gene in patients with PSP. These copy number variants include tau but few other genes within the chromosome 17 haplotype region, providing additional support for the direct pathogenicity of MAPT in PSP. CONCLUSIONS: Clinicians should also be aware of MAPT duplication as a possible genetic cause of PSP, especially in patients presenting with young age at onset. © 2019 International Parkinson and Movement Disorder Society.

Epigenome-Wide Association Study (EWAS) of Blood Lipids in Healthy Population from STANISLAS Family Study (SFS).

Epigenome-Wide Association Studies (EWAS) are furthering our knowledge of epigenetic modifications involved in the regulation of lipids' metabolism. Furthermore, epigenetic patterns associated with lipid levels may play an important role in predicting the occurrence of cardiovascular events. To further investigate the relationship between methylation status and lipids, we performed an EWAS in 211 individuals from the STANISLAS Family study (SFS). Methylation at two CpG sites (PRKAG2; p = 1.39 × 10-8; KREMEN2; p = 5.75 × 10-9) were significantly associated with lipidomic profiles. Replication was sought in adipose tissue where one probe, cg08897188, was found to be nominally significant (KREMEN2; p = 0.0196). These results could provide new insight in the mechanisms underlying cardiovascular diseases and contribute to new therapeutic interventions.

A sequence variant associated with sortilin-1 (SORT1) on 1p13.3 is independently associated with abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a common human disease with a high estimated heritability (0.7); however, only a small number of associated genetic loci have been reported to date. In contrast, over 100 loci have now been reproducibly associated with either blood lipid profile and/or coronary artery disease (CAD) (both risk factors for AAA) in large-scale meta-analyses. This study employed a staged design to investigate whether the loci for these two phenotypes are also associated with AAA. Validated CAD and dyslipidaemia loci underwent screening using the Otago AAA genome-wide association data set. Putative associations underwent staged secondary validation in 10 additional cohorts. A novel association between the SORT1 (1p13.3) locus and AAA was identified. The rs599839 G allele, which has been previously associated with both dyslipidaemia and CAD, reached genome-wide significance in 11 combined independent cohorts (meta-analysis with 7048 AAA cases and 75 976 controls: G allele OR 0.81, 95% CI 0.76-0.85, P = 7.2 × 10(-14)). Modelling for confounding interactions of concurrent dyslipidaemia, heart disease and other risk factors suggested that this marker is an independent predictor of AAA susceptibility. In conclusion, a genetic marker associated with cardiovascular risk factors, and in particular concurrent vascular disease, appeared to independently contribute to susceptibility for AAA. Given the potential genetic overlap between risk factor and disease phenotypes, the use of well-characterized case-control cohorts allowing for modelling of cardiovascular disease risk confounders will be an important component in the future discovery of genetic markers for conditions such as AAA.

Detection, imputation, and association analysis of small deletions and null alleles on oligonucleotide arrays.

Copy-number variation (CNV) is a major contributor to human genetic variation. Recently, CNV associations with human disease have been reported. Many genome-wide association (GWA) studies in complex diseases have been performed with sets of biallelic single-nucleotide polymorphisms (SNPs), but the available CNV methods are still limited. We present a new method (TriTyper) that can infer genotypes in case-control data sets for deletion CNVs, or SNPs with an extra, untyped allele at a high-resolution single SNP level. By accounting for linkage disequilibrium (LD), as well as intensity data, calling accuracy is improved. Analysis of 3102 unrelated individuals with European descent, genotyped with Illumina Infinium BeadChips, resulted in the identification of 1880 SNPs with a common untyped allele, and these SNPs are in strong LD with neighboring biallelic SNPs. Simulations indicate our method has superior power to detect associations compared to biallelic SNPs that are in LD with these SNPs, yet without increasing type I errors, as shown in a GWA analysis in celiac disease. Genotypes for 1204 triallelic SNPs could be fully imputed, with only biallelic-genotype calls, permitting association analysis of these SNPs in many published data sets. We estimate that 682 of the 1655 unique loci reflect deletions; this is on average 99 deletions per individual, four times greater than those detected by other methods. Whereas the identified loci are strongly enriched for known deletions, 61% have not been reported before. Genes overlapping with these loci more often have paralogs (p = 0.006) and biologically interact with fewer genes than expected (p = 0.004).

Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia.

Many common diseases are accompanied by disturbances in biochemical traits. Identifying the genetic determinants could provide novel insights into disease mechanisms and reveal avenues for developing new therapies. Here, we report a genome-wide association analysis for commonly measured serum and urine biochemical traits. As part of the WTCCC, 500,000 SNPs genome wide were genotyped in 1955 hypertensive individuals characterized for 25 serum and urine biochemical traits. For each trait, we assessed association with individual SNPs, adjusting for age, sex, and BMI. Lipid measurements were further examined in a meta-analysis of genome-wide data from a type 2 diabetes scan. The most promising associations were examined in two epidemiological cohorts. We discovered association between serum urate and SLC2A9, a glucose transporter (p = 2 x 10(-15)) and confirmed this in two independent cohorts, GRAPHIC study (p = 9 x 10(-15)) and TwinsUK (p = 8 x 10(-19)). The odds ratio for hyperuricaemia (defined as urate >0.4 mMol/l) is 1.89 (95% CI = 1.36-2.61) per copy of common allele. We also replicated many genes previously associated with serum lipids and found previously recognized association between LDL levels and SNPs close to genes encoding PSRC1 and CELSR2 (p = 1 x 10(-7)). The common allele was associated with a 6% increase in nonfasting serum LDL. This region showed increased association in the meta-analysis (p = 4 x 10(-14)). This finding provides a potential biological mechanism for the recent association of this same allele of the same SNP with increased risk of coronary disease.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease.

OBJECTIVE: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay.

BACKGROUND: High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome. RESULTS: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available. CONCLUSIONS: Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.

Collaborative meta-analysis: associations of 150 candidate genes with osteoporosis and osteoporotic fracture.

BACKGROUND: Osteoporosis is a highly heritable trait. Many candidate genes have been proposed as being involved in regulating bone mineral density (BMD). Few of these findings have been replicated in independent studies. OBJECTIVE: To assess the relationship between BMD and fracture and all common single-nucleotide polymorphisms (SNPs) in previously proposed osteoporosis candidate genes. DESIGN: Large-scale meta-analysis of genome-wide association data. SETTING: 5 international, multicenter, population-based studies. PARTICIPANTS: Data on BMD were obtained from 19 195 participants (14 277 women) from 5 populations of European origin. Data on fracture were obtained from a prospective cohort (n = 5974) from the Netherlands. MEASUREMENTS: Systematic literature review using the Human Genome Epidemiology Navigator identified autosomal genes previously evaluated for association with osteoporosis. We explored the common SNPs arising from the haplotype map of the human genome (HapMap) across all these genes. BMD at the femoral neck and lumbar spine was measured by dual-energy x-ray absorptiometry. Fractures were defined as clinically apparent, site-specific, validated nonvertebral and vertebral low-energy fractures. RESULTS: 150 candidate genes were identified and 36 016 SNPs in these loci were assessed. SNPs from 9 gene loci (ESR1, LRP4, ITGA1, LRP5, SOST, SPP1, TNFRSF11A, TNFRSF11B, and TNFSF11) were associated with BMD at either site. For most genes, no SNP was statistically significant. For statistically significant SNPs (n = 241), effect sizes ranged from 0.04 to 0.18 SD per allele. SNPs from the LRP5, SOST, SPP1, and TNFRSF11A loci were significantly associated with fracture risk; odds ratios ranged from 1.13 to 1.43 per allele. These effects on fracture were partially independent of BMD at SPP1 and SOST. LIMITATION: Only common polymorphisms in linkage disequilibrium with SNPs in HapMap could be assessed, and previously reported associations for SNPs in some candidate genes could not be excluded. CONCLUSION: In this large-scale collaborative genome-wide meta-analysis, 9 of 150 candidate genes were associated with regulation of BMD, 4 of which also significantly affected risk for fracture. However, most candidate genes had no consistent association with BMD.

LDL-cholesterol concentrations: a genome-wide association study.

BACKGROUND: LDL cholesterol has a causal role in the development of cardiovascular disease. Improved understanding of the biological mechanisms that underlie the metabolism and regulation of LDL cholesterol might help to identify novel therapeutic targets. We therefore did a genome-wide association study of LDL-cholesterol concentrations. METHODS: We used genome-wide association data from up to 11,685 participants with measures of circulating LDL-cholesterol concentrations across five studies, including data for 293 461 autosomal single nucleotide polymorphisms (SNPs) with a minor allele frequency of 5% or more that passed our quality control criteria. We also used data from a second genome-wide array in up to 4337 participants from three of these five studies, with data for 290,140 SNPs. We did replication studies in two independent populations consisting of up to 4979 participants. Statistical approaches, including meta-analysis and linkage disequilibrium plots, were used to refine association signals; we analysed pooled data from all seven populations to determine the effect of each SNP on variations in circulating LDL-cholesterol concentrations. FINDINGS: In our initial scan, we found two SNPs (rs599839 [p=1.7x10(-15)] and rs4970834 [p=3.0x10(-11)]) that showed genome-wide statistical association with LDL cholesterol at chromosomal locus 1p13.3. The second genome screen found a third statistically associated SNP at the same locus (rs646776 [p=4.3x10(-9)]). Meta-analysis of data from all studies showed an association of SNPs rs599839 (combined p=1.2x10(-33)) and rs646776 (p=4.8x10(-20)) with LDL-cholesterol concentrations. SNPs rs599839 and rs646776 both explained around 1% of the variation in circulating LDL-cholesterol concentrations and were associated with about 15% of an SD change in LDL cholesterol per allele, assuming an SD of 1 mmol/L. INTERPRETATION: We found evidence for a novel locus for LDL cholesterol on chromosome 1p13.3. These results potentially provide insight into the biological mechanisms that underlie the regulation of LDL cholesterol and might help in the discovery of novel therapeutic targets for cardiovascular disease.

The novel EPTP repeat defines a superfamily of proteins implicated in epileptic disorders.

Recent studies suggest that mutations in the LGI1/Epitempin gene cause autosomal dominant lateral temporal epilepsy. This gene encodes a protein of unknown function, which we postulate is secreted. The LGI1 protein has leucine-rich repeats in the N-terminal sequence and a tandem repeat (which we named EPTP) in its C-terminal region. A redefinition of the C-terminal repeat and the application of sensitive sequence analysis methods enabled us to define a new superfamily of proteins carrying varying numbers of the novel EPTP repeats in combination with various extracellular domains. Genes encoding proteins of this family are located in genomic regions associated with epilepsy and other neurological disorders.

Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals.

SCOPE: Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1ß inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors. METHODS: Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance. RESULTS: SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL-1 (SE ± 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (ß ± SE = -0.0058 ± 0.002, p = 0.004) to increase insulin by 0.0058 IU mL-1 , per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression. CONCLUSION: Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants.

High-throughput genotyping of Salmonella enterica serovar Typhi allowing geographical assignment of haplotypes and pathotypes within an urban District of Jakarta, Indonesia.

High-throughput epidemiological typing systems that provide phylogenetic and genotypic information are beneficial for tracking bacterial pathogens in the field. The incidence of Salmonella enterica serovar Typhi infection in Indonesia is high and is associated with atypical phenotypic traits such as expression of the j and the z66 flagellum antigens. Utilizing a high-throughput genotyping platform to investigate known nucleotide polymorphisms dispersed around the genome, we determined the haplotypes of 140 serovar Typhi isolates associated with Indonesia. We identified nine distinct serovar Typhi haplotypes circulating in Indonesia for more than 30 years, with eight of these present in a single Jakarta suburb within a 2-year period. One dominant haplotype, H59, is associated with j and z66 flagellum expression, representing a potential pathotype unique to Indonesia. Phylogenetic analysis suggests that H59 z66(+), j(+) isolates emerged relatively recently in terms of the origin of serovar Typhi and are geographically restricted. These data demonstrate the potential of high-throughput genotyping platforms for analyzing serovar Typhi populations in the field. The study also provides insight into the evolution of serovar Typhi and demonstrates the value of a molecular epidemiological technique that is exchangeable, that is internet friendly, and that has global utility.

A genotype calling algorithm for the Illumina BeadArray platform.

MOTIVATION: Large-scale genotyping relies on the use of unsupervised automated calling algorithms to assign genotypes to hybridization data. A number of such calling algorithms have been recently established for the Affymetrix GeneChip genotyping technology. Here, we present a fast and accurate genotype calling algorithm for the Illumina BeadArray genotyping platforms. As the technology moves towards assaying millions of genetic polymorphisms simultaneously, there is a need for an integrated and easy-to-use software for calling genotypes. RESULTS: We have introduced a model-based genotype calling algorithm which does not rely on having prior training data or require computationally intensive procedures. The algorithm can assign genotypes to hybridization data from thousands of individuals simultaneously and pools information across multiple individuals to improve the calling. The method can accommodate variations in hybridization intensities which result in dramatic shifts of the position of the genotype clouds by identifying the optimal coordinates to initialize the algorithm. By incorporating the process of perturbation analysis, we can obtain a quality metric measuring the stability of the assigned genotype calls. We show that this quality metric can be used to identify SNPs with low call rates and accuracy. AVAILABILITY: The C++ executable for the algorithm described here is available by request from the authors.

Genome-wide associations of gene expression variation in humans.

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

The 9th Santorini Conference: Systems Medicine, Personalised Health and Therapy. "The Odyssey from Hope to Practice", Santorini, Greece, 30 September⁻3 October 2018.

The 9th traditional biannual conference on Systems Medicine, Personalised Health & Therapy-"The Odyssey from Hope to Practice", inspired by the Greek mythology, was a call to search for practical solutions in cardio-metabolic diseases and cancer, to resolve and overcome the obstacles in modern medicine by creating more interactions among disciplines, as well as between academic and industrial research, directed towards an effective 'roadmap' for personalised health and therapy. The 9th Santorini Conference, under the Presidency of Sofia Siest, the director of the INSERM U1122; IGE-PCV (www.u1122.inserm.fr), University of Lorraine, France, offered a rich and innovative scientific program. It gathered 34 worldwide distinguished speakers, who shared their passion for personalised medicine with 160 attendees in nine specific sessions on the following topics: First day: The Odyssey from hope to practice: Personalised medicine-landmarks and challenges Second day: Diseases to therapeutics-genotype to phenotype an "-OMICS" approach: focus on personalised therapy and precision medicine Third day: Gene-environment interactions and pharmacovigilance: a pharmacogenetics approach for deciphering disease "bench to clinic to reality" Fourth day: Pharmacogenomics to drug discovery: a big data approach and focus on clinical data and clinical practice. In this article we present the topics shared among the participants of the conference and we highlight the key messages.

Joint genome-wide association study of progressive supranuclear palsy identifies novel susceptibility loci and genetic correlation to neurodegenerative diseases.

BACKGROUND: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease for which the genetic contribution is incompletely understood. METHODS: We conducted a joint analysis of 5,523,934 imputed SNPs in two newly-genotyped progressive supranuclear palsy cohorts, primarily derived from two clinical trials (Allon davunetide and NNIPPS riluzole trials in PSP) and a previously published genome-wide association study (GWAS), in total comprising 1646 cases and 10,662 controls of European ancestry. RESULTS: We identified 5 associated loci at a genome-wide significance threshold P < 5 × 10- 8, including replication of 3 loci from previous studies and 2 novel loci at 6p21.1 and 12p12.1 (near RUNX2 and SLCO1A2, respectively). At the 17q21.31 locus, stepwise regression analysis confirmed the presence of multiple independent loci (localized near MAPT and KANSL1). An additional 4 loci were highly suggestive of association (P < 1 × 10- 6). We analyzed the genetic correlation with multiple neurodegenerative diseases, and found that PSP had shared polygenic heritability with Parkinson's disease and amyotrophic lateral sclerosis. CONCLUSIONS: In total, we identified 6 additional significant or suggestive SNP associations with PSP, and discovered genetic overlap with other neurodegenerative diseases. These findings clarify the pathogenesis and genetic architecture of PSP.

Sequencing and association analysis of the type 1 diabetes-linked region on chromosome 10p12-q11.

BACKGROUND: In an effort to locate susceptibility genes for type 1 diabetes (T1D) several genome-wide linkage scans have been undertaken. A chromosomal region designated IDDM10 retained genome-wide significance in a combined analysis of the main linkage scans. Here, we studied sequence polymorphisms in 23 Mb on chromosome 10p12-q11, including the putative IDDM10 region, to identify genes associated with T1D. RESULTS: Initially, we resequenced the functional candidate genes, CREM and SDF1, located in this region, genotyped 13 tag single nucleotide polymorphisms (SNPs) and found no association with T1D. We then undertook analysis of the whole 23 Mb region. We constructed and sequenced a contig tile path from two bacterial artificial clone libraries. By comparison with a clone library from an unrelated person used in the Human Genome Project, we identified 12,058 SNPs. We genotyped 303 SNPs and 25 polymorphic microsatellite markers in 765 multiplex T1D families and followed up 22 associated polymorphisms in up to 2,857 families. We found nominal evidence of association in six loci (P = 0.05 - 0.0026), located near the PAPD1 gene. Therefore, we resequenced 38.8 kb in this region, found 147 SNPs and genotyped 84 of them in the T1D families. We also tested 13 polymorphisms in the PAPD1 gene and in five other loci in 1,612 T1D patients and 1,828 controls from the UK. Overall, only the D10S193 microsatellite marker located 28 kb downstream of PAPD1 showed nominal evidence of association in both T1D families and in the case-control sample (P = 0.037 and 0.03, respectively). CONCLUSION: We conclude that polymorphisms in the CREM and SDF1 genes have no major effect on T1D. The weak T1D association that we detected in the association scan near the PAPD1 gene may be either false or due to a small genuine effect, and cannot explain linkage at the IDDM10 region.