92 research outputs found

    Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging

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    Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition

    Connecting the dots: Potential of data integration to identify regulatory snps in late-onset alzheimer's disease GWAS findings

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    Late-onset Alzheimer's disease (LOAD) is a multifactorial disorder with over twenty loci associated with disease risk. Given the number of genome-wide significant variants that fall outside of coding regions, it is possible that some of these variants alter some function of gene expression rather than tagging coding variants that alter protein structure and/or function. RegulomeDB is a database that annotates regulatory functions of genetic variants. In this study, we utilized RegulomeDB to investigate potential regulatory functions of lead single nucleotide polymorphisms (SNPs) identified in five genome-wide association studies (GWAS) of risk and age-at onset (AAO) of LOAD, as well as SNPs in LD (r2≥0.80) with the lead GWAS SNPs. Of a total 614 SNPs examined, 394 returned RegulomeDB scores of 1-6. Of those 394 variants, 34 showed strong evidence of regulatory function (RegulomeDB score ,3), and only 3 of them were genome-wide significant SNPs (ZCWPW1/ rs1476679, CLU/rs1532278 and ABCA7/rs3764650). This study further supports the assumption that some of the non-coding GWAS SNPs are true associations rather than tagged associations and demonstrates the application of RegulomeDB to GWAS data.©2014 Rosenthal et al

    Specificity of the STAT4 Genetic Association for Severe Disease Manifestations of Systemic Lupus Erythematosus

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    Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. A polymorphism in the STAT4 gene has recently been established as a risk factor for SLE, but the relationship with specific SLE subphenotypes has not been studied. We studied 137 SNPs in the STAT4 region genotyped in 4 independent SLE case series (total n = 1398) and 2560 healthy controls, along with clinical data for the cases. Using conditional testing, we confirmed the most significant STAT4 haplotype for SLE risk. We then studied a SNP marking this haplotype for association with specific SLE subphenotypes, including autoantibody production, nephritis, arthritis, mucocutaneous manifestations, and age at diagnosis. To prevent possible type-I errors from population stratification, we reanalyzed the data using a subset of subjects determined to be most homogeneous based on principal components analysis of genome-wide data. We confirmed that four SNPs in very high LD (r2 = 0.94 to 0.99) were most strongly associated with SLE, and there was no compelling evidence for additional SLE risk loci in the STAT4 region. SNP rs7574865 marking this haplotype had a minor allele frequency (MAF) = 31.1% in SLE cases compared with 22.5% in controls (OR = 1.56, p = 10−16). This SNP was more strongly associated with SLE characterized by double-stranded DNA autoantibodies (MAF = 35.1%, OR = 1.86, p<10−19), nephritis (MAF = 34.3%, OR = 1.80, p<10−11), and age at diagnosis<30 years (MAF = 33.8%, OR = 1.77, p<10−13). An association with severe nephritis was even more striking (MAF = 39.2%, OR = 2.35, p<10−4 in the homogeneous subset of subjects). In contrast, STAT4 was less strongly associated with oral ulcers, a manifestation associated with milder disease. We conclude that this common polymorphism of STAT4 contributes to the phenotypic heterogeneity of SLE, predisposing specifically to more severe disease

    Association analysis of PON2 genetic variants with serum paraoxonase activity and systemic lupus erythematosus

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    <p>Abstract</p> <p>Background</p> <p>Low serum paraoxonase (PON) activity is associated with the risk of coronary artery disease, diabetes and systemic lupus erythematosus (SLE). Our prior studies have shown that the <it>PON1</it>/rs662 (p.Gln192Arg), <it>PON1</it>/rs854560 (p.Leu55Met), <it>PON3</it>/rs17884563 and <it>PON3</it>/rs740264 SNPs (single nucleotide polymorphisms) significantly affect serum PON activity. Since <it>PON1, PON2 </it>and <it>PON3 </it>share high degree of structural and functional properties, in this study, we examined the role of <it>PON2 </it>genetic variation on serum PON activity, risk of SLE and SLE-related clinical manifestations in a Caucasian case-control sample.</p> <p>Methods</p> <p><it>PON2 </it>SNPs were selected from HapMap and SeattleSNPs databases by including at least one tagSNP from each bin defined in these resources. A total of nineteen <it>PON2 </it>SNPs were successfully genotyped in 411 SLE cases and 511 healthy controls using pyrosequencing, restriction fragment length polymorphism (RFLP) or TaqMan allelic discrimination methods.</p> <p>Results</p> <p>Our pair-wise linkage disequilibrium (LD) analysis, using an <it>r</it><sup><it>2 </it></sup>cutoff of 0.7, identified 14 <it>PON2 </it>tagSNPs that captured all 19 <it>PON2 </it>variants in our sample, 12 of which were not in high LD with known <it>PON1 </it>and <it>PON3 </it>SNP modifiers of PON activity. Stepwise regression analysis of PON activity, including the known modifiers, identified five <it>PON2 </it>SNPs [rs6954345 (p.Ser311Cys), rs13306702, rs987539, rs11982486, and rs4729189; <it>P </it>= 0.005 to 2.1 × 10<sup>-6</sup>] that were significantly associated with PON activity. We found no association of <it>PON2 </it>SNPs with SLE risk but modest associations were observed with lupus nephritis (rs11981433, rs17876205, rs17876183) and immunologic disorder (rs11981433) in SLE patients (<it>P </it>= 0.013 to 0.042).</p> <p>Conclusions</p> <p>Our data indicate that <it>PON2 </it>genetic variants significantly affect variation in serum PON activity and have modest effects on risk of lupus nephritis and SLE-related immunologic disorder.</p

    Differential genetic associations for systemic lupus erythematosus based on anti-dsDNA autoantibody production

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    Systemic lupus erythematosus (SLE) is a clinically heterogeneous, systemic autoimmune disease characterized by autoantibody formation. Previously published genome-wide association studies (GWAS) have investigated SLE as a single phenotype. Therefore, we conducted a GWAS to identify genetic factors associated with anti-dsDNA autoantibody production, a SLE-related autoantibody with diagnostic and clinical importance. Using two independent datasets, over 400,000 single nucleotide polymorphisms (SNPs) were studied in a total of 1,717 SLE cases and 4,813 healthy controls. Anti-dsDNA autoantibody positive (anti-dsDNA +, n = 811) and anti-dsDNA autoantibody negative (anti-dsDNA -, n = 906) SLE cases were compared to healthy controls and to each other to identify SNPs associated specifically with these SLE subtypes. SNPs in the previously identified SLE susceptibility loci STAT4, IRF5, ITGAM, and the major histocompatibility complex were strongly associated with anti-dsDNA + SLE. Far fewer and weaker associations were observed for anti-dsDNA - SLE. For example, rs7574865 in STAT4 had an OR for anti-dsDNA + SLE of 1.77 (95% CI 1.57-1.99, p = 2.0E-20) compared to an OR for anti-dsDNA - SLE of 1.26 (95% CI 1.12-1.41, p = 2.4E-04), with pheterogeneity<0.0005. SNPs in the SLE susceptibility loci BANK1, KIAA1542, and UBE2L3 showed evidence of association with anti-dsDNA + SLE and were not associated with anti-dsDNA - SLE. In conclusion, we identified differential genetic associations with SLE based on anti-dsDNA autoantibody production. Many previously identified SLE susceptibility loci may confer disease risk through their role in autoantibody production and be more accurately described as autoantibody propensity loci. Lack of strong SNP associations may suggest that other types of genetic variation or non-genetic factors such as environmental exposures have a greater impact on susceptibility to anti-dsDNA - SLE

    Analysis of shared heritability in common disorders of the brain

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    ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

    A novel Alzheimer disease locus located near the gene encoding tau protein

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordAPOE ε4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ε4+ (10 352 cases and 9207 controls) and APOE ε4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ε4 status. Suggestive associations (P<1 × 10-4) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ε4+: 1250 cases and 536 controls; APOE ε4-: 718 cases and 1699 controls). Among APOE ε4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10-9). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ε4+ subjects (CR1 and CLU) or APOE ε4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10-7) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P≤1.3 × 10-8), frontal cortex (P≤1.3 × 10-9) and temporal cortex (P≤1.2 × 10-11). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10-6) and temporal cortex (P=2.6 × 10-6). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ε4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted
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