medizinische genetik

, Volume 22, Issue 2, pp 235–241 | Cite as

Online-Datenbanken und systematische Metaanalysen komplex-genetischer Erkrankungen

Schwerpunkt

Zusammenfassung

Die Suszeptibilität komplex-genetischer Erkrankungen wird durch eine unbekannte Anzahl genetischer Faktoren bestimmt. In den letzten Jahrzehnten sind Hunderte von Suszeptibilitätsloci für die Alzheimer-Krankheit (AD), das idiopathische Parkinson-Syndrom (PD), Schizophrenie (SZ) und multiple Sklerose (MS) beschrieben worden. Diese schwierig zu überschauende Datenlage für jede dieser Erkrankungen wird kompliziert durch die ansteigende Zahl genomweiter Assoziationsstudien. Um die Evaluation und Interpretation der Ergebnisse zu erleichtern, haben wir Internet-Datenbanken für genetische Assoziationsstudien in AD, PD, SZ und MS generiert. Neben einer detailierten Synopse aller verfügbaren Studien bieten die Datenbanken allel-basierte Metaanalysen der Polymorphismen, zu denen ausreichende Daten vorliegen. In diesem Review stellen wir anhand der Datenbanken für AD (AlzGene) und PD (PDGene) den Hintergrund und die Implikationen dieses Ansatzes vor.

Schlüsselwörter

Neuropsychiatrische Erkrankungen Alzheimer-Krankheit Idiopathisches Parkinson-Syndrom Genetische Assoziation Metaanalyse 

Verzeichnis der verwendeten Abkürzungen

AD

Alzheimer-Krankheit

APOE

„apolipoprotein E“ (Gen-Name)

BDNF

„brain-derived neurotrophic factor“ (Gen-Name)

CLU

„clusterin“ (Gen-Name)

CR1

„complement component (3b/4b) receptor 1“ (Gen-Name)

GBA

„glucosidase, beta, acid“ (Gen-Name)

GWAS

Genomweite Assoziationsstudie

LRRK2

„leucine-rich repeat kinase 2“ (Gen-Name)

MAPT

„microtubule-associated protein tau“ (Gen-Name)

MS

Multiple Sklerose

OR

Odds Ratio (Effektstärke)

PD

Idiopathisches Parkinson-Syndrom

PICALM

„phosphatidylinositol binding clathrin assembly protein“ (Gen-Name)

SNCA

„alpha-synuclein“ (Gen-Name)

SZ

Schizophrenie

TPRG1

„tumor protein p63 regulated 1“ (Gen-Name)

ε4Allel

Epsilon-4-Allel

Online databases and systematic meta-analyses of genetically complex diseases

Abstract

Susceptibility to genetically complex disorders is determined by an unknown number of genetic determinants, and decades of intensive research have yielded hundreds of such potential susceptibility loci for Alzheimer’s disease (AD), Parkinson’s disease (PD), schizophrenia (SZ), and multiple sclerosis (MS). The results of genome-wide association studies are now adding to an already vast and complicated body of data. To facilitate the evaluation and interpretation of these findings, we have recently created online databases for genetic association studies in AD, PD, SZ, and MS. In addition to providing detailed summaries for each eligible study, the databases present the results of allele-based meta-analyses for all polymorphisms with sufficient genotype data. In this review, we discuss the background and implications of the database approach developed by our group, using current findings from the AD (AlzGene) and PD (PDGene) databases as examples.

Keywords

Neuropsychiatric traits Alzheimer’s disease Idiopathic Parkinson’s disease Genetic association Meta-analysis 

Literatur

  1. 1.
    Bertram L, McQueen MB, Mullin K et al (2007) Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet 39:17–23CrossRefPubMedGoogle Scholar
  2. 2.
    Allen NC, Bagade S, McQueen MB et al (2008) Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet 40:827–834CrossRefPubMedGoogle Scholar
  3. 3.
    Bertram L, Tanzi RE (2009) Genome-wide association studies in Alzheimer’s disease. Hum Mol Genet 18:R137–R145CrossRefPubMedGoogle Scholar
  4. 4.
    Lambert JC, Heath S, Even G et al (2009) Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nat Genet 41:1094–1099CrossRefPubMedGoogle Scholar
  5. 5.
    Harold D, Abraham R, Hollingworth P et al (2009) Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat Genet 41:1088–1093CrossRefPubMedGoogle Scholar
  6. 6.
    Ioannidis JP, Boffetta P, Little J et al (2008) Assessment of cumulative evidence on genetic associations: interim guidelines. Int J Epidemiol 37:120–132CrossRefPubMedGoogle Scholar
  7. 7.
    Reiman EM, Webster JA, Myers AJ et al (2007) GAB2 alleles modify Alzheimer’s risk in APOE epsilon4 carriers. Neuron 54:713–720CrossRefPubMedGoogle Scholar
  8. 8.
    Li H, Wetten S, Li L et al (2008) Candidate single-nucleotide polymorphisms from a genomewide association study of Alzheimer disease. Arch Neurol 65:45–53CrossRefPubMedGoogle Scholar
  9. 9.
    Lohmueller KE, Pearce CL, Pike M et al (2003) Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 33:177–182CrossRefPubMedGoogle Scholar
  10. 10.
    Bertram L, Tanzi RE (2008) Thirty years of Alzheimer’s disease genetics: the implications of systematic meta-analyses. Nat Rev Neurosci 9:768–778CrossRefPubMedGoogle Scholar
  11. 11.
    De Jager PL, Chibnik LB, Cui J et al (2009) Integration of genetic risk factors into a clinical algorithm for multiple sclerosis susceptibility: a weighted genetic risk score. Lancet Neurol 8:1111–1119CrossRefGoogle Scholar
  12. 12.
    Ioannidis JP (2009) Prediction of cardiovascular disease outcomes and established cardiovascular risk factors by genome-wide association markers. Circ Cardiovasc Genet 2:7–15CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Neuropsychiatrische GenetikMax-Planck-Institut für Molekulare GenetikBerlinDeutschland
  2. 2.Klinik und Poliklinik für NeurologieJohannes Gutenberg-UniversitätMainzDeutschland

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