Publications by authors named "Bahram Namjou"

45 Publications

Validation of low-coverage whole-genome sequencing for mitochondrial DNA variants suggests mitochondrial DNA as a genetic cause of preterm birth.

Hum Mutat 2021 Dec 8;42(12):1602-1614. Epub 2021 Sep 8.

Division of Human Genetics, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.

Preterm birth (PTB), or birth that occurs earlier than 37 weeks of gestational age, is a major contributor to infant mortality and neonatal hospitalization. Mutations in the mitochondrial genome (mtDNA) have been linked to various rare mitochondrial disorders and may be a contributing factor in PTB given that maternal genetic factors have been strongly linked to PTB. However, to date, no study has found a conclusive connection between a particular mtDNA variant and PTB. Given the high mtDNA copy number per cell, an automated pipeline was developed for detecting mtDNA variants using low-coverage whole-genome sequencing (lcWGS) data. The pipeline was first validated against samples of known heteroplasmy, and then applied to 929 samples from a PTB cohort from diverse ethnic backgrounds with an average gestational age of 27.18 weeks (range: 21-30). Our new pipeline successfully identified haplogroups and a large number of mtDNA variants in this large PTB cohort, including 8 samples carrying known pathogenic variants and 47 samples carrying rare mtDNA variants. These results confirm that lcWGS can be utilized to reliably identify mtDNA variants. These mtDNA variants may make a contribution toward preterm birth in a small proportion of live births.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/humu.24279DOI Listing
December 2021

Genome-wide association studies of low back pain and lumbar spinal disorders using electronic health record data identify a locus associated with lumbar spinal stenosis.

Pain 2021 08;162(8):2263-2272

Genomic Medicine Institute, Geisinger, Danville, PA, United States.

Abstract: Identifying genetic risk factors for lumbar spine disorders may lead to knowledge regarding underlying mechanisms and the development of new treatments. We conducted a genome-wide association study involving 100,811 participants with genotypes and longitudinal electronic health record data from the Electronic Medical Records and Genomics Network and Geisinger Health. Cases and controls were defined using validated algorithms and clinical diagnostic codes. Electronic health record-defined phenotypes included low back pain requiring healthcare utilization (LBP-HC), lumbosacral radicular syndrome (LSRS), and lumbar spinal stenosis (LSS). Genome-wide association study used logistic regression with additive genetic effects adjusting for age, sex, site-specific factors, and ancestry (principal components). A fixed-effect inverse-variance weighted meta-analysis was conducted. Genetic variants of genome-wide significance (P < 5 × 10-8) were carried forward for replication in an independent sample from UK Biobank. Phenotype prevalence was 48.8% for LBP-HC, 19.8% for LSRS, and 7.9% for LSS. No variants were significantly associated with LBP-HC. One locus was associated with LSRS (lead variant rs146153280:C>G, odds ratio [OR] = 1.17 for G, P = 2.1 × 10-9), but was not replicated. Another locus on chromosome 2 spanning GFPT1, NFU1, and AAK1 was associated with LSS (lead variant rs13427243:G>A, OR = 1.10 for A, P = 4.3 × 10-8) and replicated in UK Biobank (OR = 1.11, P = 5.4 × 10-5). This was the first genome-wide association study meta-analysis of lumbar spinal disorders using electronic health record data. We identified 2 novel associations with LSRS and LSS; the latter was replicated in an independent sample.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/j.pain.0000000000002221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277660PMC
August 2021

SLE non-coding genetic risk variant determines the epigenetic dysfunction of an immune cell specific enhancer that controls disease-critical microRNA expression.

Nat Commun 2021 01 8;12(1):135. Epub 2021 Jan 8.

Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai, 200001, China.

Since most variants that impact polygenic disease phenotypes localize to non-coding genomic regions, understanding the consequences of regulatory element variants will advance understanding of human disease mechanisms. Here, we report that the systemic lupus erythematosus (SLE) risk variant rs2431697 as likely causal for SLE through disruption of a regulatory element, modulating miR-146a expression. Using epigenomic analysis, genome-editing and 3D chromatin structure analysis, we show that rs2431697 tags a cell-type dependent distal enhancer specific for miR-146a that physically interacts with the miR-146a promoter. NF-kB binds the disease protective allele in a sequence-specific manner, increasing expression of this immunoregulatory microRNA. Finally, CRISPR activation-based modulation of this enhancer in the PBMCs of SLE patients attenuates type I interferon pathway activation by increasing miR-146a expression. Our work provides a strategy to define non-coding RNA functional regulatory elements using disease-associated variants and provides mechanistic links between autoimmune disease risk genetic variation and disease etiology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-20460-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794586PMC
January 2021

Evaluation of the MC4R gene across eMERGE network identifies many unreported obesity-associated variants.

Int J Obes (Lond) 2021 01 20;45(1):155-169. Epub 2020 Sep 20.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA.

Background/objectives: Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus.

Subjects/methods: The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping.

Results: Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10, Beta = -0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI.

Conclusions: MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41366-020-00675-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7752751PMC
January 2021

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

Am J Hum Genet 2020 09 5;107(3):432-444. Epub 2020 Aug 5.

School of Public Health, Imperial College London, London SW7 2AZ, UK.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2020.07.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477007PMC
September 2020

Pleiotropy in the Genetic Predisposition to Rheumatoid Arthritis: A Phenome-Wide Association Study and Inverse Variance-Weighted Meta-Analysis.

Arthritis Rheumatol 2020 09 6;72(9):1483-1492. Epub 2020 Aug 6.

Vanderbilt University Medical Center and Vanderbilt University School of Medicine, Nashville, Tennessee.

Objective: This study was undertaken to investigate the hypothesis that a genetic predisposition toward rheumatoid arthritis (RA) increases the risk of 10 cardiometabolic and autoimmune disorders previously associated with RA in epidemiologic studies, and to define new genetic pleiotropy present in RA.

Methods: Two approaches were used to test our hypothesis. First, we constructed a weighted genetic risk score (wGRS) and then examined its association with 10 prespecified disorders. Additionally, a phenome-wide association study (PheWAS) was carried out to identify potential new associations. Second, inverse variance-weighted regression (IVWR) meta-analysis was used to characterize the association between genetic susceptibility to RA and the prespecified disorders, with the results expressed as odds ratios (ORs) and 95% confidence intervals (95% CIs).

Results: The wGRS for RA was significantly associated with type 1 diabetes mellitus (DM) (OR 1.10 [95% CI 1.04-1.16]; P = 9.82 × 10 ) and multiple sclerosis (OR 0.82 [95% CI 0.77-0.88]; P = 1.73 × 10 ), but not with other cardiometabolic phenotypes. In the PheWAS, wGRS was also associated with an increased risk of several autoimmune phenotypes including RA, thyroiditis, and systemic sclerosis, and with a decreased risk of demyelinating disorders. In the IVWR meta-analyses, RA was significantly associated with an increased risk of type 1 DM (P = 1.15 × 10 ), with evidence of horizontal pleiotropy (Mendelian Randomization-Egger intercept estimate P = 0.001) likely driven by rs2476601, a PTPN22 variant. The association between type 1 DM and RA remained significant (P = 9.53 × 10 ) after excluding rs2476601, with no evidence of horizontal pleiotropy (intercept estimate P = 0.939). RA was also significantly associated with type 2 DM and C-reactive protein levels. These associations were driven by variation in the major histocompatibility complex region.

Conclusion: This study presents evidence of pleiotropy between the genetic predisposition to RA and associated phenotypes found in other autoimmune and cardiometabolic disorders, including type 1 DM.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/art.41291DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7572512PMC
September 2020

A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies.

J Clin Endocrinol Metab 2020 06;105(6)

Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.

Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice.

Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment.

Design, Patients, And Methods: Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS.

Results: The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity", "type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension", and "sleep apnea" reaching phenome-wide significance.

Conclusions: Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1210/clinem/dgz326DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453038PMC
June 2020

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization.

World J Surg 2020 01;44(1):84-94

The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Background: The extent to which obesity and genetics determine postoperative complications is incompletely understood.

Methods: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components.

Results: Individuals with overweight or obese BMI (≥25 kg/m) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10), and people with obesity (BMI ≥ 30 kg/m) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures.

Conclusions: Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00268-019-05202-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925615PMC
January 2020

GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network.

BMC Med 2019 07 17;17(1):135. Epub 2019 Jul 17.

Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati School of Medicine, Cincinnati, OH, USA.

Background: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition.

Methods: First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI).

Results: Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10). This effect was consistent in both pediatric (p = 9.92 × 10) and adult (p = 9.73 × 10) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses.

Conclusions: In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12916-019-1364-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636057PMC
July 2019

A phenome-wide association study to discover pleiotropic effects of , , and .

NPJ Genom Med 2019 11;4. Epub 2019 Feb 11.

20Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449 USA.

We conducted an electronic health record (EHR)-based phenome-wide association study (PheWAS) to discover pleiotropic effects of variants in three lipoprotein metabolism genes , , and . Using high-density genotype data, we tested the associations of variants in the three genes with 1232 EHR-derived binary phecodes in 51,700 European-ancestry (EA) individuals and 585 phecodes in 10,276 African-ancestry (AA) individuals; 457 , 730 , and 720 variants were filtered by imputation quality (  > 0.4), minor allele frequency (>1%), linkage disequilibrium (  < 0.3), and association with LDL-C levels, yielding a set of two , three , and five variants in EA but no variants in AA. Cases and controls were defined for each phecode using the PheWAS package in R. Logistic regression assuming an additive genetic model was used with adjustment for age, sex, and the first two principal components. Significant associations were tested in additional cohorts from Vanderbilt University ( = 29,713), the Marshfield Clinic Personalized Medicine Research Project ( = 9562), and UK Biobank ( = 408,455). We identified one , two , and two variants significantly associated with an examined phecode. Only one of the variants was associated with a non-lipid disease phecode, ("myopia") but this association was not significant in the replication cohorts. In this large-scale PheWAS we did not find LDL-C-related variants in , , and to be associated with non-lipid-related phenotypes including diabetes, neurocognitive disorders, or cataracts.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41525-019-0078-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370860PMC
February 2019

Probing the Virtual Proteome to Identify Novel Disease Biomarkers.

Circulation 2018 11;138(22):2469-2481

Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (E.W.K.).

Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals.

Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651).

Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β.

Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/CIRCULATIONAHA.118.036063DOI Listing
November 2018

A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers.

Nat Commun 2018 08 30;9(1):3522. Epub 2018 Aug 30.

Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.

Defining the full spectrum of human disease associated with a biomarker is necessary to advance the biomarker into clinical practice. We hypothesize that associating biomarker measurements with electronic health record (EHR) populations based on shared genetic architectures would establish the clinical epidemiology of the biomarker. We use Bayesian sparse linear mixed modeling to calculate SNP weightings for 53 biomarkers from the Atherosclerosis Risk in Communities study. We use the SNP weightings to computed predicted biomarker values in an EHR population and test associations with 1139 diagnoses. Here we report 116 associations meeting a Bonferroni level of significance. A false discovery rate (FDR)-based significance threshold reveals more known and undescribed associations across a broad range of biomarkers, including biometric measures, plasma proteins and metabolites, functional assays, and behaviors. We confirm an inverse association between LDL-cholesterol level and septicemia risk in an independent epidemiological cohort. This approach efficiently discovers biomarker-disease associations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-05624-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117367PMC
August 2018

A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus.

Hum Mol Genet 2018 07;27(13):2392-2404

Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA.

Systemic lupus erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared with the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/hmg/ddy140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005081PMC
July 2018

Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder.

PLoS One 2016 29;11(7):e0159621. Epub 2016 Jul 29.

Harvard Medical School, Pediatrics, Boston, Massachusetts, United States of America.

Objective: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD.

Methods: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children's Hospital (BCH) (N = 150) and Cincinnati Children's Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups.

Results: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children's Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters.

Conclusions: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0159621PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966969PMC
August 2017

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.

Appl Clin Inform 2016 07 20;7(3):693-706. Epub 2016 Jul 20.

Todd Lingren, Cincinnati Children's Hospital Medical Center, Biomedical Informatics, 3333 Burnet Avenue, MLC 7024 Cincinnati, OH 45229-3039, Phone: 513-803-9032, Fax: 513-636-2056, Email:

Objective: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR).

Introduction: Childhood obesity increases risk factors for cardiovascular morbidity and vascular disease. Accurate definition of a high precision phenotype through a standardize tool is critical to the success of large-scale genomic studies and validating rare monogenic variants causing severe early onset obesity.

Data And Methods: Rule based and machine learning based algorithms were developed using structured and unstructured data from two EHR databases from Boston Children's Hospital (BCH) and Cincinnati Children's Hospital and Medical Center (CCHMC). Exclusion criteria including medications or comorbid diagnoses were defined. Machine learning algorithms were developed using cross-site training and testing in addition to experimenting with natural language processing features.

Results: Precision was emphasized for a high fidelity cohort. The rule-based algorithm performed the best overall, 0.895 (CCHMC) and 0.770 (BCH). The best feature set for machine learning employed Unified Medical Language System (UMLS) concept unique identifiers (CUIs), ICD-9 codes, and RxNorm codes.

Conclusions: Detecting severe early childhood obesity is essential for the intervention potential in children at the highest long-term risk of developing comorbidities related to obesity and excluding patients with underlying pathological and non-syndromic causes of obesity assists in developing a high-precision cohort for genetic study. Further such phenotyping efforts inform future practical application in health care environments utilizing clinical decision support.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.4338/ACI-2016-01-RA-0015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5052543PMC
July 2016

A GWAS Study on Liver Function Test Using eMERGE Network Participants.

PLoS One 2015 28;10(9):e0138677. Epub 2015 Sep 28.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, United States of America; University of Cincinnati, College of Medicine, Cincinnati, OH, United States of America; U.S. Department of Veterans Affairs Medical Center, Cincinnati, OH, United States of America.

Introduction: Liver enzyme levels and total serum bilirubin are under genetic control and in recent years genome-wide population-based association studies have identified different susceptibility loci for these traits. We conducted a genome-wide association study in European ancestry participants from the Electronic Medical Records and Genomics (eMERGE) Network dataset of patient medical records with available genotyping data in order to identify genetic contributors to variability in serum bilirubin levels and other liver function tests and to compare the effects between adult and pediatric populations.

Methods: The process of whole genome imputation of eMERGE samples with standard quality control measures have been described previously. After removing missing data and outliers based on principal components (PC) analyses, 3294 samples from European ancestry were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and total serum bilirubin and other liver function tests was tested using linear regression, adjusting for age, gender, site, platform and ancestry principal components (PC).

Results: Consistent with previous results, a strong association signal has been detected for UGT1A gene cluster (best SNP rs887829, beta = 0.15, p = 1.30x10-118) for total serum bilirubin level. Indeed, in this region more than 176 SNPs (or indels) had p<10-8 spanning 150Kb on the long arm of chromosome 2q37.1. In addition, we found a similar level of magnitude in a pediatric group (p = 8.26x10-47, beta = 0.17). Further imputation using sequencing data as a reference panel revealed association of other markers including known TA7 repeat indels (rs8175347) (p = 9.78x10-117) and rs111741722 (p = 5.41x10-119) which were in proxy (r2 = 0.99) with rs887829. Among rare variants, two Asian subjects homozygous for coding SNP rs4148323 (G71R) were identified. Additional known effects for total serum bilirubin were also confirmed including organic anion transporters SLCO1B1-SLCO1B3, TDRP and ZMYND8 at FDR<0.05 with no gene-gene interaction effects. Phenome-wide association studies (PheWAS) suggest a protective effect of TA7 repeat against cerebrovascular disease in an adult cohort (OR = 0.75, p = 0.0008). Among other liver function tests, we also confirmed the previous effect of the ABO blood group locus for variation in serum alkaline phosphatase (rs579459, p = 9.44x10-15).

Conclusions: Taken together, our data present interesting findings with strong confirmation of previous effects by simply using the eMERGE electronic health record phenotyping. In addition, our findings indicate that similar to the adult population, the UGT1A1 is the main locus responsible for normal variation of serum bilirubin in pediatric populations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138677PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586138PMC
June 2016

Lupus Risk Variant Increases pSTAT1 Binding and Decreases ETS1 Expression.

Am J Hum Genet 2015 May 9;96(5):731-9. Epub 2015 Apr 9.

Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA; Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; Oklahoma City Veterans Affairs Medical Center, Oklahoma City, OK 73104, USA.

Genetic variants at chromosomal region 11q23.3, near the gene ETS1, have been associated with systemic lupus erythematosus (SLE), or lupus, in independent cohorts of Asian ancestry. Several recent studies have implicated ETS1 as a critical driver of immune cell function and differentiation, and mice deficient in ETS1 develop an SLE-like autoimmunity. We performed a fine-mapping study of 14,551 subjects from multi-ancestral cohorts by starting with genotyped variants and imputing to all common variants spanning ETS1. By constructing genetic models via frequentist and Bayesian association methods, we identified 16 variants that are statistically likely to be causal. We functionally assessed each of these variants on the basis of their likelihood of affecting transcription factor binding, miRNA binding, or chromatin state. Of the four variants that we experimentally examined, only rs6590330 differentially binds lysate from B cells. Using mass spectrometry, we found more binding of the transcription factor signal transducer and activator of transcription 1 (STAT1) to DNA near the risk allele of rs6590330 than near the non-risk allele. Immunoblot analysis and chromatin immunoprecipitation of pSTAT1 in B cells heterozygous for rs6590330 confirmed that the risk allele increased binding to the active form of STAT1. Analysis with expression quantitative trait loci indicated that the risk allele of rs6590330 is associated with decreased ETS1 expression in Han Chinese, but not other ancestral cohorts. We propose a model in which the risk allele of rs6590330 is associated with decreased ETS1 expression and increases SLE risk by enhancing the binding of pSTAT1.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2015.03.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570281PMC
May 2015

Autoantibodies targeting glomerular annexin A2 identify patients with proliferative lupus nephritis.

Proteomics Clin Appl 2015 Dec 12;9(11-12):1012-20. Epub 2015 Jun 12.

Department of Medicine, University of Louisville School of Medicine, Louisville, KY, USA.

Purpose: Patients with systemic lupus erythematosus (SLE) frequently develop lupus nephritis (LN), a complication frequently leading to end stage kidney disease. Immune complex deposition in the glomerulus is central to the development of LN. Using a targeted proteomic approach, we tested the hypothesis that autoantibodies targeting glomerular antigens contribute to the development of LN.

Experimental Design: Human podocyte and glomerular proteins were separated by SDS-PAGE and immunoblotted with sera from SLE patients with and without LN. The regions of those gels corresponding to reactive bands observed with sera from LN patients were analyzed using LC-MS/MS.

Results: LN reactive bands were seen at approximately 50 kDa in podocyte extracts and between 36 and 50 kDa in glomerular extracts. Those bands were analyzed by LC-MS/MS and 102 overlapping proteins were identified. Bioinformatic analysis determined that 36 of those proteins were membrane associated, including a protein previously suggested to contribute to glomerulonephritis and LN, annexin A2. By ELISA, patients with proliferative LN demonstrated significantly increased antibodies against annexin A2.

Conclusion And Clinical Relevance: Proteomic approaches identified multiple candidate antigens for autoantibodies in patients with LN. Serum antibodies against annexin A2 were significantly elevated in subjects with proliferative LN, validating those antibodies as potential biomarkers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/prca.201400175DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4690797PMC
December 2015

Lupus risk variants in the PXK locus alter B-cell receptor internalization.

Front Genet 2014 8;5:450. Epub 2015 Jan 8.

Department of Medicine, Johns Hopkins University School of Medicine Baltimore, MD, USA.

Genome wide association studies have identified variants in PXK that confer risk for humoral autoimmune diseases, including systemic lupus erythematosus (SLE or lupus), rheumatoid arthritis and more recently systemic sclerosis. While PXK is involved in trafficking of epidermal growth factor Receptor (EGFR) in COS-7 cells, mechanisms linking PXK to lupus pathophysiology have remained undefined. In an effort to uncover the mechanism at this locus that increases lupus-risk, we undertook a fine-mapping analysis in a large multi-ancestral study of lupus patients and controls. We define a large (257kb) common haplotype marking a single causal variant that confers lupus risk detected only in European ancestral populations and spans the promoter through the 3' UTR of PXK. The strongest association was found at rs6445972 with P < 4.62 × 10(-10), OR 0.81 (0.75-0.86). Using stepwise logistic regression analysis, we demonstrate that one signal drives the genetic association in the region. Bayesian analysis confirms our results, identifying a 95% credible set consisting of 172 variants spanning 202 kb. Functionally, we found that PXK operates on the B-cell antigen receptor (BCR); we confirmed that PXK influenced the rate of BCR internalization. Furthermore, we demonstrate that individuals carrying the risk haplotype exhibited a decreased rate of BCR internalization, a process known to impact B cell survival and cell fate. Taken together, these data define a new candidate mechanism for the genetic association of variants around PXK with lupus risk and highlight the regulation of intracellular trafficking as a genetically regulated pathway mediating human autoimmunity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fgene.2014.00450DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288052PMC
January 2015

The effect of inversion at 8p23 on BLK association with lupus in Caucasian population.

PLoS One 2014 29;9(12):e115614. Epub 2014 Dec 29.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), 3333 Burnet Avenue, Cincinnati, OH, 45229, United States of America; University of Cincinnati, College of Medicine, Cincinnati, OH, United States of America; Department of Veteran Affairs Medical Center, Cincinnati, OH, United States of America.

Unlabelled: To explore the potential influence of the polymorphic 8p23.1 inversion on known autoimmune susceptibility risk at or near BLK locus, we validated a new bioinformatics method that utilizes SNP data to enable accurate, high-throughput genotyping of the 8p23.1 inversion in a Caucasian population.

Methods: Principal components analysis (PCA) was performed using markers inside the inversion territory followed by k-means cluster analyses on 7416 European derived and 267 HapMaP CEU and TSI samples. A logistic regression conditional analysis was performed.

Results: Three subgroups have been identified; inversion homozygous, heterozygous and non-inversion homozygous. The status of inversion was further validated using HapMap samples that had previously undergone Fluorescence in situ hybridization (FISH) assays with a concordance rate of above 98%. Conditional analyses based on the status of inversion were performed. We found that overall association signals in the BLK region remain significant after controlling for inversion status. The proportion of lupus cases and controls (cases/controls) in each subgroup was determined to be 0.97 for the inverted homozygous group (1067 cases and 1095 controls), 1.12 for the inverted heterozygous group (1935 cases 1717 controls) and 1.36 for non-inverted subgroups (924 cases and 678 controls). After calculating the linkage disequilibrium between inversion status and lupus risk haplotype we found that the lupus risk haplotype tends to reside on non-inversion background. As a result, a new association effect between non-inversion status and lupus phenotype has been identified ((p = 8.18×10(-7), OR = 1.18, 95%CI = 1.10-1.26).

Conclusion: Our results demonstrate that both known lupus risk haplotype and inversion status act additively in the pathogenesis of lupus. Since inversion regulates expression of many genes in its territory, altered expression of other genes might also be involved in the development of lupus.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0115614PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4278715PMC
September 2015

Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis.

Front Genet 2014 18;5:401. Epub 2014 Nov 18.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; College of Medicine, University of Cincinnati Cincinnati, OH, USA ; U.S. Department of Veterans Affairs Medical Center Cincinnati, OH, USA.

Objective: We report the first pediatric specific Phenome-Wide Association Study (PheWAS) using electronic medical records (EMRs). Given the early success of PheWAS in adult populations, we investigated the feasibility of this approach in pediatric cohorts in which associations between a previously known genetic variant and a wide range of clinical or physiological traits were evaluated. Although computationally intensive, this approach has potential to reveal disease mechanistic relationships between a variant and a network of phenotypes.

Method: Data on 5049 samples of European ancestry were obtained from the EMRs of two large academic centers in five different genotyped cohorts. Recently, these samples have undergone whole genome imputation. After standard quality controls, removing missing data and outliers based on principal components analyses (PCA), 4268 samples were used for the PheWAS study. We scanned for associations between 2476 single-nucleotide polymorphisms (SNP) with available genotyping data from previously published GWAS studies and 539 EMR-derived phenotypes. The false discovery rate was calculated and, for any new PheWAS findings, a permutation approach (with up to 1,000,000 trials) was implemented.

Results: This PheWAS found a variety of common variants (MAF > 10%) with prior GWAS associations in our pediatric cohorts including Juvenile Rheumatoid Arthritis (JRA), Asthma, Autism and Pervasive Developmental Disorder (PDD) and Type 1 Diabetes with a false discovery rate < 0.05 and power of study above 80%. In addition, several new PheWAS findings were identified including a cluster of association near the NDFIP1 gene for mental retardation (best SNP rs10057309, p = 4.33 × 10(-7), OR = 1.70, 95%CI = 1.38 - 2.09); association near PLCL1 gene for developmental delays and speech disorder [best SNP rs1595825, p = 1.13 × 10(-8), OR = 0.65(0.57 - 0.76)]; a cluster of associations in the IL5-IL13 region with Eosinophilic Esophagitis (EoE) [best at rs12653750, p = 3.03 × 10(-9), OR = 1.73 95%CI = (1.44 - 2.07)], previously implicated in asthma, allergy, and eosinophilia; and association of variants in GCKR and JAZF1 with allergic rhinitis in our pediatric cohorts [best SNP rs780093, p = 2.18 × 10(-5), OR = 1.39, 95%CI = (1.19 - 1.61)], previously demonstrated in metabolic disease and diabetes in adults.

Conclusion: The PheWAS approach with re-mapping ICD-9 structured codes for our European-origin pediatric cohorts, as with the previous adult studies, finds many previously reported associations as well as presents the discovery of associations with potentially important clinical implications.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fgene.2014.00401DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235428PMC
December 2014

The IRF5-TNPO3 association with systemic lupus erythematosus has two components that other autoimmune disorders variably share.

Hum Mol Genet 2015 Jan 8;24(2):582-96. Epub 2014 Sep 8.

Clinical Immunology Unit, Department of Internal Medicine, Stavanger University Hospital, Stavanger, Norway.

Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5-TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10(-49); OR = 1.38-1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10(-27)-10(-32), OR = 1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5-TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/hmg/ddu455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4275071PMC
January 2015

EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children.

Front Genet 2013 3;4:268. Epub 2013 Dec 3.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; School of Medicine, University of Cincinnati Cincinnati, OH, USA ; Department of Veteran Affairs Medical Center Cincinnati, OH, USA.

Unlabelled: Common variations at the loci harboring the fat mass and obesity gene (FTO), MC4R, and TMEM18 are consistently reported as being associated with obesity and body mass index (BMI) especially in adult population. In order to confirm this effect in pediatric population five European ancestry cohorts from pediatric eMERGE-II network (CCHMC-BCH) were evaluated.

Method: Data on 5049 samples of European ancestry were obtained from the Electronic Medical Records (EMRs) of two large academic centers in five different genotyped cohorts. For all available samples, gender, age, height, and weight were collected and BMI was calculated. To account for age and sex differences in BMI, BMI z-scores were generated using 2000 Centers of Disease Control and Prevention (CDC) growth charts. A Genome-wide association study (GWAS) was performed with BMI z-score. After removing missing data and outliers based on principal components (PC) analyses, 2860 samples were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and BMI was tested using linear regression adjusting for age, gender, and PC by cohort. The effects of SNPs were modeled assuming additive, recessive, and dominant effects of the minor allele. Meta-analysis was conducted using a weighted z-score approach.

Results: The mean age of subjects was 9.8 years (range 2-19). The proportion of male subjects was 56%. In these cohorts, 14% of samples had a BMI ≥95 and 28 ≥ 85%. Meta analyses produced a signal at 16q12 genomic region with the best result of p = 1.43 × 10(-) (7) [p (rec) = 7.34 × 10(-) (8)) for the SNP rs8050136 at the first intron of FTO gene (z = 5.26) and with no heterogeneity between cohorts (p = 0.77). Under a recessive model, another published SNP at this locus, rs1421085, generates the best result [z = 5.782, p (rec) = 8.21 × 10(-) (9)]. Imputation in this region using dense 1000-Genome and Hapmap CEU samples revealed 71 SNPs with p < 10(-) (6), all at the first intron of FTO locus. When hetero-geneity was permitted between cohorts, signals were also obtained in other previously identified loci, including MC4R (rs12964056, p = 6.87 × 10(-) (7), z = -4.98), cholecystokinin CCK (rs8192472, p = 1.33 × 10(-) (6), z = -4.85), Interleukin 15 (rs2099884, p = 1.27 × 10(-) (5), z = 4.34), low density lipoprotein receptor-related protein 1B [LRP1B (rs7583748, p = 0.00013, z = -3.81)] and near transmembrane protein 18 (TMEM18) (rs7561317, p = 0.001, z = -3.17). We also detected a novel locus at chromosome 3 at COL6A5 [best SNP = rs1542829, minor allele frequency (MAF) of 5% p = 4.35 × 10(-) (9), z = 5.89].

Conclusion: An EMR linked cohort study demonstrates that the BMI-Z measurements can be successfully extracted and linked to genomic data with meaningful confirmatory results. We verified the high prevalence of childhood rate of overweight and obesity in our cohort (28%). In addition, our data indicate that genetic variants in the first intron of FTO, a known adult genetic risk factor for BMI, are also robustly associated with BMI in pediatric population.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fgene.2013.00268DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3847941PMC
December 2013

PTPN22 association in systemic lupus erythematosus (SLE) with respect to individual ancestry and clinical sub-phenotypes.

PLoS One 2013 7;8(8):e69404. Epub 2013 Aug 7.

Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America.

Protein tyrosine phosphatase non-receptor type 22 (PTPN22) is a negative regulator of T-cell activation associated with several autoimmune diseases, including systemic lupus erythematosus (SLE). Missense rs2476601 is associated with SLE in individuals with European ancestry. Since the rs2476601 risk allele frequency differs dramatically across ethnicities, we assessed robustness of PTPN22 association with SLE and its clinical sub-phenotypes across four ethnically diverse populations. Ten SNPs were genotyped in 8220 SLE cases and 7369 controls from in European-Americans (EA), African-Americans (AA), Asians (AS), and Hispanics (HS). We performed imputation-based association followed by conditional analysis to identify independent associations. Significantly associated SNPs were tested for association with SLE clinical sub-phenotypes, including autoantibody profiles. Multiple testing was accounted for by using false discovery rate. We successfully imputed and tested allelic association for 107 SNPs within the PTPN22 region and detected evidence of ethnic-specific associations from EA and HS. In EA, the strongest association was at rs2476601 (P = 4.7 × 10(-9), OR = 1.40 (95% CI = 1.25-1.56)). Independent association with rs1217414 was also observed in EA, and both SNPs are correlated with increased European ancestry. For HS imputed intronic SNP, rs3765598, predicted to be a cis-eQTL, was associated (P = 0.007, OR = 0.79 and 95% CI = 0.67-0.94). No significant associations were observed in AA or AS. Case-only analysis using lupus-related clinical criteria revealed differences between EA SLE patients positive for moderate to high titers of IgG anti-cardiolipin (aCL IgG >20) versus negative aCL IgG at rs2476601 (P = 0.012, OR = 1.65). Association was reinforced when these cases were compared to controls (P = 2.7 × 10(-5), OR = 2.11). Our results validate that rs2476601 is the most significantly associated SNP in individuals with European ancestry. Additionally, rs1217414 and rs3765598 may be associated with SLE. Further studies are required to confirm the involvement of rs2476601 with aCL IgG.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0069404PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737240PMC
August 2014

Evaluation of TRAF6 in a large multiancestral lupus cohort.

Arthritis Rheum 2012 Jun 9;64(6):1960-9. Epub 2012 Jan 9.

Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

Objective: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with significant immune system aberrations resulting from complex heritable genetics as well as environmental factors. We undertook to study the role of TRAF6 as a candidate gene for SLE, since it plays a major role in several signaling pathways that are important for immunity and organ development.

Methods: Fifteen single-nucleotide polymorphisms (SNPs) across TRAF6 were evaluated in 7,490 SLE patients and 6,780 control subjects from different ancestries. Population-based case-control association analyses and meta-analyses were performed. P values, false discovery rate q values, and odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated.

Results: Evidence of associations was detected in multiple SNPs. The best overall P values were obtained for SNPs rs5030437 and rs4755453 (P = 7.85 × 10(-5) and P = 4.73 × 10(-5) , respectively) without significant heterogeneity among populations (P = 0.67 and P = 0.50, respectively, in Q statistic). In addition, SNP rs540386, which was previously reported to be associated with rheumatoid arthritis (RA), was found to be in linkage disequilibrium with these 2 SNPs (r(2) = 0.95) and demonstrated evidence of association with SLE in the same direction (meta-analysis P = 9.15 × 10(-4) , OR 0.89 [95% CI 0.83-0.95]). The presence of thrombocytopenia improved the overall results in different populations (meta-analysis P = 1.99 × 10(-6) , OR 0.57 [95% CI 0.45-0.72], for rs5030470). Finally, evidence of family-based association in 34 African American pedigrees with the presence of thrombocytopenia was detected in 1 available SNP (rs5030437) with a Z score magnitude of 2.28 (P = 0.02) under a dominant model.

Conclusion: Our data indicate the presence of association of TRAF6 with SLE, consistent with the previous report of association with RA. These data provide further support for the involvement of TRAF6 in the pathogenesis of autoimmunity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/art.34361DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3380425PMC
June 2012

The genetics of systemic lupus erythematosus and implications for targeted therapy.

Ann Rheum Dis 2011 Mar;70 Suppl 1:i37-43

Rheumatology Division, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.

Observations of familial aggregation (λs=8-29) and a 40% identical twin concordance rate prompted recent work towards a comprehensive genetic analysis of systemic lupus erythematosus (SLE). Since 2007, the number of genetic effects known to be associated with human lupus has increased by fivefold, underscoring the complexity of inheritance that probably contributes to this disease. Approximately 35 genes associated with lupus have either been replicated in multiple samples or are near the threshold for genome-wide significance (p > 5 x 10⁻⁸). Some are rare variants that convincingly contribute to lupus only in specific subgroups. Strong associations have been found with a large haplotype block in the human leucocyte antigen region, with Fcγ receptors, and with genes coding for complement components, in which a single gene deletion may cause SLE in rare familial cases and copy number variation is more common in the larger population of SLE patients. Examples of newly discovered genes include ITGAM, STAT4 and MECP2/IRAK1. Ongoing studies to build models in which combinations of associated genes might contribute to specific disease manifestations should contribute to improved understanding of disease pathology. In addition, pharmacogenomic components of ongoing clinical trials are likely to provide insights into fundamental disease pathology as well as contributing to informed patient selection for targeted treatments and biomarkers to guide dosing and gauge responsiveness. Besides these potentially valuable new insights into the pathophysiology of an enigmatic, potentially deadly, and, as yet, unsolved disease, genetic studies are likely to suggest novel molecular targets for strategic development of safer and more effective therapeutics.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/ard.2010.138057DOI Listing
March 2011

The lupus family registry and repository.

Rheumatology (Oxford) 2011 Jan 23;50(1):47-59. Epub 2010 Sep 23.

Arthritis and Immunology Research Program, Oklahoma Medical Research Foundation, Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

The Lupus Family Registry and Repository (LFRR) was established with the goal of assembling and distributing materials and data from families with one or more living members diagnosed with SLE, in order to address SLE genetics. In the present article, we describe the problems and solutions of the registry design and biometric data gathering; the protocols implemented to guarantee data quality and protection of participant privacy and consent; and the establishment of a local and international network of collaborators. At the same time, we illustrate how the LFRR has enabled progress in lupus genetics research, answering old scientific questions while laying out new challenges in the elucidation of the biologic mechanisms that underlie disease pathogenesis. Trained staff ascertain SLE cases, unaffected family members and population-based controls, proceeding in compliance with the relevant laws and standards; participant consent and privacy are central to the LFRR's effort. Data, DNA, serum, plasma, peripheral blood and transformed B-cell lines are collected and stored, and subject to strict quality control and safety measures. Coded data and materials derived from the registry are available for approved scientific users. The LFRR has contributed to the discovery of most of the 37 genetic associations now known to contribute to lupus through 104 publications. The LFRR contains 2618 lupus cases from 1954 pedigrees that are being studied by 76 approved users and their collaborators. The registry includes difficult to obtain populations, such as multiplex pedigrees, minority patients and affected males, and constitutes the largest collection of lupus pedigrees in the world. The LFRR is a useful resource for the discovery and characterization of genetic associations in SLE.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/rheumatology/keq302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3307518PMC
January 2011

Male-only systemic lupus.

J Rheumatol 2010 Jul 15;37(7):1480-7. Epub 2010 May 15.

Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.

Objective: Systemic lupus erythematosus (SLE) is more common among women than men, a ratio of about 10 to 1. We undertook this study to describe familial male SLE within a large familial SLE cohort.

Methods: SLE families (2 or more patients) were identified from the Lupus Multiplex Registry and Repository. Genomic DNA and blood samples were obtained using standard methods. Autoantibodies were determined by multiple methods. Medical records were abstracted for SLE clinical data. Fluorescent in situ hybridization (FISH) was performed with X and Y centromere-specific probes, and a probe specific for the Toll-like receptor 7 gene on the X chromosome.

Results: Among 523 SLE families, we found 5 families in which all the SLE patients were male. FISH found no yaa gene equivalent in these families. SLE-unaffected primary female relatives from the 5 families with only-male SLE patients had a statistically increased rate of positive antinuclear antibodies compared to SLE-unaffected female relatives in other families. White men with SLE were 5 times more likely to have an offspring with SLE than White women with SLE, but there was no difference in this likelihood among Black men.

Conclusion: Because women in the all-male families had positive antinuclear antibodies, and men are more likely to have children with SLE, these data suggest genetic susceptibility factors that act only in men.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3899/jrheum.090726DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978923PMC
July 2010

Interferon-gamma gene polymorphisms associated with susceptibility to systemic lupus erythematosus.

Ann Rheum Dis 2010 Jun 16;69(6):1247-50. Epub 2009 Nov 16.

Department of Biological Sciences, KAIST, 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Korea.

Objective: Interferon-gamma (IFNG) is a type II interferon playing diverse roles in innate and adaptive immune systems. Elevated expression of IFNG has been associated with systemic lupus erythematosus (SLE). This study examined the association of IFNG polymorphisms with SLE susceptibility.

Methods: Five tag single-nucleotide polymorphisms (SNP) and eight variations in all known regulatory sequences affecting IFNG expression within and around IFNG were genotyped in 1759 unrelated Korean subjects. SLE susceptibility association was assessed by comparing 742 SLE patients and 1017 unaffected controls using multivariate logistic regression analysis with adjustment for age and gender.

Results: SLE susceptibility association was significant with rs2069705 in the promoter (adjusted OR 2.27, p=0.0024) and marginal with rs3181032 in the promoter (p=0.037), rs2430561 in intron 1 (p=0.022) and rs2069718 in intron 3 (p=0.026) in a recessive genetic model. Five other SNP showed no association and four other variations were not polymorphic.

Conclusion: Several SNP in IFNG are associated with SLE susceptibility, and the risk allele of an associated SNP (rs2430561) located in an NF-kappaB binding site has elevated IFNG expression versus the non-risk allele, supporting that elevated IFNG expression is associated with increased SLE susceptibility.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/ard.2009.117572DOI Listing
June 2010
-->