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Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease

Abstract

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1,2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

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Figure 1: Summary of the main genetic findings.
Figure 2: Most of the PLD3 coding variants are located in exon 11, and the Ala442Ala variant affects splicing.
Figure 3: PLD3 affects APP processing.

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The authors declare competing financial interests: details are available in the online version of the paper. Exome-sequencing data is available on NIAGADs (https://www.niagads.org, accession number NG00033).

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Acknowledgements

We thank M. Frohman for providing us with PLD1- and PLD2-WT constructs as well as constructs for the inactive mutations in these genes. This work was supported by grants from the National Institutes of Health (P30-NS069329, R01-AG044546 and R01-AG035083), the Alzheimer Association (NIRG-11-200110) and Barnes Jewish Foundation. This research was conducted while C.C. was a recipient of a New Investigator Award in Alzheimer’s Disease from the American Federation for Aging Research. C.C. is a recipient of a BrightFocus Foundation Alzheimer's Disease Research Grant (A2013359S). Sequencing of some of the families included in this study was supported by Genentech and Pfizer. The recruitment and clinical characterization of research participants at Washington University were supported by NIH P50 AG05681, P01 AG03991 and P01 AG026276. This work was supported in part by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Department of Health and Human Services, project ZO1 AG000950-11. Samples from the National Cell Repository for Alzheimer’s Disease (NCRAD) and NIA-LOAD, which receives government support under a cooperative agreement (U24 AG21886; U24: 5U24AG026395 and 1R01AG041797), were used in this study. We thank our contributors, including the Alzheimer’s Disease Centers, that collected samples used in this study, as well as participants and their families, whose help and participation made this work possible. The Cache County Study is supported by National Institutes of Health, RO1-AG11380, RO1-AG18712 and RO1-AG21136. Genotyping and analysis conducted at Brigham Young University was funded by grants from the National Institutes of Health R01-AG042611 and the Alzheimer’s Association (MNIRG-11-205368) to J.S.K.K. The sequencing at University of Washington was supported by NIH R01039700 (Z.B.). The sequencing for the NIA-UK samples was supported by the Alzheimer’s Research UK (ARUK), by an anonymous donor, by the NINDS (ZO1 AG000950-10), by the Wellcome Trust/MRC Joint Call in Neurodegeneration award (WT089698) to the UK Parkinson's Disease Consortium (UKPDC), by the Big Lottery (to K.M.) and by a fellowship from ARUK to R.G Some samples and pathological diagnoses were provided by the MRC London Neurodegenerative Diseases Brain Bank and the Manchester Brain Bank from Brains for Dementia Research, jointly funded from ARUK and AS via ABBUK Ltd. This work was also supported by the NIHR Queen Square Dementia BRU and BRC NIHR grant mechanisms. The sample recruitment and genetic studies at University of Pittsburgh are funded by NIH grants AG041718, AG030653, AG005133, AG07562 and AG023652. The Toronto sample studies are funded by Canadian Institutes of Health Research, Wellcome Trust, Medical Research Council, National Institute of Health, National Institute of Health Research, Ontario Research Fund and Alzheimer Society of Ontario (to P.S.G.-H.). The Nottingham Laboratory (K.M.) is funded by ARUK and Big Lottery. ARUK is supported by the UK Medical Research Council through the MRC Sudden Death Brain Bank (C.S.) and by a Project Grant (G0901254) and Training Fellowship (G0802462 to M.R.). P.P. receives funds from the Department of Health of the Government of Navarra, Spain (13085 and 3/2008) and from the UTE project FIMA, Spain. J.T.T. receives funds from the NIA (R01AG21136).

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Contributions

All the authors read and approved the manuscript. C.C. conceived and designed the experiments, supervised research, wrote the manuscript, performed the family and sample selection for exome-sequencing, and analysed the data. C.M.K., S.H., J.C. and A.T.J. performed all the cell-based analysis, and the PLD3 total gene-expression experiments. S.C.J. performed PLD3 pool-sequencing experiments. B.A.B. performed the genotyping of Val232Met and Ala442Ala in the Knight-ADRC and NIA-LOAD data sets, and analysed public gene-expression databases and carried out bioinformatic analysis of the effect of some variants on splicing. O.H., S.B. and Y.C. performed statistical and bioinformatic analyses. J.N. and D.L. recruited and assessed the NIA-LOAD families with the PLD3 variants. J.B. T.S, D.C. and B.C. performed Sequenom genotyping. R.G., C.S., J.B., M.K.L., J.P., J.R.G., A.S., J.H. P.F., P.G.R., C.D.C., J.T.T., M.C.N., R.G.M., C.S., M.L., J.S.K.K., F.Y.D., M.N.B., X.W., O.L.L., M.G., M.I.K., C.M., J.T., J.L., A.B., I.B., K.B., K.M, O.L.B., P.P., Z.B., E.S., E.T., E.R. and P.S.G.-H., provided genotype data for the NIA-UK and NIMH datasets, Cache-County dataset, University of Pittsburgh dataset, University of Nottingham dataset, NIA-LOAD, the Wellderly dataset and the Toronto dataset. M.R. and D.G.H. performed the co-regulation pathway analysis. N.C. performed the neuropathological examination of the PLD3 Val232Met carriers. J.C.M. supervised recruitment and clinical assessment of the Knight-ADRC subjects, and A.M.G. supervised the functional and genetic experiments and critically reviewed all data and data analysis.

Corresponding author

Correspondence to Carlos Cruchaga.

Ethics declarations

Competing interests

J.C.M. has participated and is currently participating in clinical trials of antidementia drugs sponsored by Janssen Immunotherapy and Pfizer. J.C.M. has served as a consultant for Eli Lilly USA. He receives research support from Eli Lilly/Avid Radiopharmaceuticals and is funded by NIH grants P50AG005681, P01AG003991, P01AG026276 and U19AG032438. A.M.G. has received payment for lectures from Genentech and Amgen, and has served as a consultant for Finnegan LLC. She has received research support from Genentech, Pfizer and Astra Zeneca and is funded by NIH grant AG041797.

Extended data figures and tables

Extended Data Figure 1 PLD3(V232M) is associated with age at onset for Alzheimer’s disease.

a, b, Age at onset was analysed for association with the PLD3(V232M) variant in 2,220 cases and 1,841 controls from the Knight-ADRC and NIA-LOAD data sets, by the Kaplan–Meier method. Data were tested for significant differences using the log-rank test. Case-only analysis (a); the carriers of the minor allele (AG) have an AAO 3 years lower than the non-carriers (69 versus 73; P = 3 × 10−3). Controls were included as censored data (b). The carriers of the minor allele have an AAO 8 years lower than the non-carriers (70 versus 78; P = 3 × 10−3). GG, homozygous for the GG genotype for the PLD3(V232M) variant.

Extended Data Figure 2 Forest plot for each case–control series for the Val232Met variant.

Extended Data Figure 3 PLD3 and APP mRNA expression are inversely correlated.

PLD3 (probe 201050_at) and APP (probe 211277_x_at) expression levels were extracted from the GSE5281 data set. PLD3 mRNA levels are significantly lower in Alzheimer’s disease cases compared to controls (P = 8.10 × 10−10), but APP is higher in Alzheimer’s disease cases (P = 7.88 × 10−8). PLD3 mRNA levels are inversely correlated with APP mRNA expression levels (P = 1.00 × 10−16). The correlation is stronger in Alzheimer’s disease cases (Person correlation coefficient = −0.55), than in controls (Person correlation coefficient = −0.44), but in both scenarios the correlation is highly significant.

Extended Data Figure 4 PLD3 interacts with APP.

HEK293T cells were transiently transfected with vectors containing APP-WT and an empty vector (pcDNA3) or PLD3-WT for 48 h. Cell lysates were extracted in non-ionic detergent, pre-cleared with Protein A beads and immunoprecipitated with an antibody to the Myc-tag on APP (9E10). Immunoblots were probed with an antibody specific to human PLD3. PLD1 and PLD2 reportedly do not inmunoprecipitate with APP15,16.

Extended Data Table 1 Association of the PLD3(V232M) variant in seven independent case–control data sets
Extended Data Table 2 Sequence variants found in PLD3 in the NIA-LOAD, Knight-ADRC and NIA-UK data sets
Extended Data Table 3 Gene-based analysis including all coding variants or only variants predicted to be deleterious
Extended Data Table 4 Association analysis for PLD3(A442A) in four data sets of individuals of European descent
Extended Data Table 5 PLD3 is associated with risk for Alzheimer’s disease in African Americans

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Cruchaga, C., Karch, C., Jin, S. et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease. Nature 505, 550–554 (2014). https://doi.org/10.1038/nature12825

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