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Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer’s disease with OSBPL6, PTPRG, and PDCL3

Molecular Psychiatry volume 21, pages 1608–1612 (2016)Cite this article

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Abstract

The genetic basis of Alzheimer's disease (AD) is complex and heterogeneous. Over 200 highly penetrant pathogenic variants in the genes APP, PSEN1, and PSEN2 cause a subset of early-onset familial AD. On the other hand, susceptibility to late-onset forms of AD (LOAD) is indisputably associated to the ɛ4 allele in the gene APOE, and more recently to variants in more than two-dozen additional genes identified in the large-scale genome-wide association studies (GWAS) and meta-analyses reports. Taken together however, although the heritability in AD is estimated to be as high as 80%, a large proportion of the underlying genetic factors still remain to be elucidated. In this study, we performed a systematic family-based genome-wide association and meta-analysis on close to 15 million imputed variants from three large collections of AD families (~3500 subjects from 1070 families). Using a multivariate phenotype combining affection status and onset age, meta-analysis of the association results revealed three single nucleotide polymorphisms (SNPs) that achieved genome-wide significance for association with AD risk: rs7609954 in the gene PTPRG (P-value=3.98 × 10−8), rs1347297 in the gene OSBPL6 (P-value=4.53 × 10−8), and rs1513625 near PDCL3 (P-value=4.28 × 10−8). In addition, rs72953347 in OSBPL6 (P-value=6.36 × 10−7) and two SNPs in the gene CDKAL1 showed marginally significant association with LOAD (rs10456232, P-value=4.76 × 10−7; rs62400067, P-value=3.54 × 10−7). In summary, family-based GWAS meta-analysis of imputed SNPs revealed novel genomic variants in (or near) PTPRG, OSBPL6, and PDCL3 that influence risk for AD with genome-wide significance.

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Author information

Author notes

  1. C Herold and B V Hooli: These authors contributed equally to the work.

Authors and Affiliations

  1. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

    C Herold

  2. Department of Biostatistics, Harvard T.H Chan School of Public Health, Boston, MA, USA

    C Herold & C Lange

  3. Department of Neurology, Genetics and Aging Research Unit, Massachusetts General Hospital, Boston, MA, USA

    B V Hooli, K Mullin & R E Tanzi

  4. Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany

    T Liu, J T Roehr & L Bertram

  5. Department of Biomedicine, Bartholins Allé 6, Aarhus, Denmark

    M Mattheisen

  6. Computational Sciences, Janssen Research and Development, Pharmaceutical Company of Johnson and Johnson, Spring House, PA, USA

    A R Parrado

  7. School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London, UK

    L Bertram

  8. Platform for Genome Analytics, Institutes of Neurogenetics and Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany

    L Bertram

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  1. C Herold
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  2. B V Hooli
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  4. T Liu
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  7. A R Parrado
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  8. L Bertram
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  9. C Lange
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Corresponding authors

Correspondence to C Lange or R E Tanzi.

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The authors declare no conflict of interest.

Additional information

Author contributions

Herold performed pre-GWAS QC, the imputation of the GWAS datasets, statistical analysis of family-based cohorts and drafted the manuscript. Hooli processed DNA samples on human microarray, SNP genotype data generation and quality control, and drafted manuscript. Mullin performed genotyping, data generation and quality assessment. Liu assisted in the imputation of the GWAS datasets, statistical analysis of case-control datasets. Roehr performed the imputation of the various GWAS datasets. Mattheissen performed pre-GWAS QC, statistical analysis and revised the manuscript for intellectual content. Parrado performed pre-GWAS QC and statistical analysis. Bertram helped design, conceptualization, and planning of the study, and manuscript revision. Lange designed, conceptualized, planned, and oversaw the study, and helped with the meta-analysis of the GWAS studies, the GWAS approaches and plan the study. Tanzi designed, conceptualized, planned, and oversaw the study, and helped in drafting and revising the manuscript.

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Herold, C., Hooli, B., Mullin, K. et al. Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer’s disease with OSBPL6, PTPRG, and PDCL3. Mol Psychiatry 21, 1608–1612 (2016). https://doi.org/10.1038/mp.2015.218

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