BRIEF COMMUNICATIONS ARISING PLD3 gene variants and Alzheimer’s disease ARISING FROM
C. Cruchaga et al. Nature 505, 550–554 (2014); doi:10.1038/nature12825
Cruchaga et al. recently reported1 evidence for genetic association between Alzheimer’s disease risk and several rare DNA sequence variants in the phospholipase D3 gene (PLD3). The study’s lead signal Val232Met (rs145999145) co-segregated with Alzheimer’s disease in multiple affected families, and also showed association with Alzheimer’s disease risk in case–control samples; whereas two other highly conserved PLD3 variants, Ala442Ala (rs4819) and Met6Arg, showed nominal association with disease risk. Our efforts to replicate these findings in a large collection of family-based Alzheimer’s disease data failed to reveal any risk effect of PLD3 in Alzheimer’s disease. Our negative results, taken together with equally negative companion reports2–4 and recent GWAS meta-analysis results5, call for additional studies to examine the proposed role, if any, of rare variants in PLD3 on Alzheimer’s disease risk. There is a Reply to this Brief Communication Arising by Cruchaga, C. & Goate, A. M. Nature 520, http://dx.doi.org/10.1038/ nature14041 (2015). We tested all three of the previously reported PLD3 variants for association with Alzheimer’s disease in the National Institute of Mental Health Alzheimer’s Genetics Initiative Study Sample (NIMH, 439 multiplex families comprising 1,440 subjects; average onset age of patients: 72.4 6 7.7 years (s.d.))6. All tested NIMH subjects were monomorphic for the major allele of Met6Arg. While we observed a nominally significant signal for Val232Met in our analyses (P 5 0.0212, Table 1), this was due to over-transmission of the presumed risk allele to unaffected individuals in the NIMH data set (Appendix Fig. 1). This is in direct contrast to the data reported by Cruchaga et al.1, where the minor methionine (Met) allele was reported as conferring increased risk. The other proposed PLD3 risk variant, Ala442Ala, exhibited no association with risk for Alzheimer’s disease in the NIMH data set (P 5 0.779). Burden testing7 (weighted by minor allele frequency (MAF)) using all the PLD3 variants from the WGS data with MAF ,0.01 (333 variants) and ,0.05 (356 variants) did not reveal significant association with Alzheimer’s disease. Limiting the burden analyses to coding region (n 5 30) and non-synonymous coding region (n 5 10) variants also failed to show association with the disease (P 5 0.53 and 0.053; Table 1). Our nonsignificant results are in line with largely negative findings from three Comments (Heilmann et al.2, Lambert et al.3 and van der Lee et al.4) reporting on independent association data for both variants. Along these lines, fixed-effect meta-analyses across the effect estimates reported in these three Comments do not show nominally significant association with either variant: odds ratio (OR)Val232Met 5 1.29 (95% confidence interval (CI) 0.93–1.79), P 5 0.132 across 7,565 cases and 18,424 controls; ORAla442Ala 5 0.97 (95% CI 0.79–1.18), P 5 0.752 across 6,679 cases and 11,911 controls (Fig. 1). Finally, while meta-analyses across
a All data sets Validation data sets Initial data sets
OR 1.62 1.29 2.44
95% Cl (1.24, 2.10) (0.93, 1.79) (1.57, 3.79)
Data-set-specific ORs Ref. 4, Iceland (AGES) Ref. 4, Netherlands (Dutch AD centres) Ref. 4, Netherlands (GRIP) Ref. 4, Netherlands (RS) Ref. 4, USA (ADNI) Ref. 4, USA (FHS) Ref. 3, France Ref. 2, Germany (Bonn) Ref. 2 Spain (Barcelona) Ref. 1, 2014, Canada (Toronto) Ref. 1, 2014, UK (Nottingham) Ref. 1, 2014, USA (Cache County) Ref. 1, 2014, USA (Knight-ADRC) Ref. 1, 2014, USA (NIA-LOAD) Ref. 1, 2014, USA (Pittsburgh)
3.18 1.55 1.58 1.43 2.94 2.63 1.17 0.49 1.23 4.71 1.05 2.03 6.63 3.09 1.82
(0.17, 58.73) (0.25, 9.38) (0.25, 9.91) (0.51, 4.03) (0.63, 13.80) (0.71, 9.70) (0.67, 2.04) (0.15, 1.65) (0.67, 2.26) (0.54, 40.89) (0.26, 4.25) (0.83, 4.95) (1.52, 28.91) (1.41, 6.79) (0.70, 4.73)
I2 6 0 0
0.2
b All data sets Validation data sets Initial data sets
OR 1.19 0.97 2.25
95% Cl (1.01, 1.42) (0.79, 1.18) (1.59, 3.17)
Data-set-specific ORs Ref. 4, Netherlands (Dutch AD centres) Ref. 4, USA (ADNI) Ref. 3, France Ref. 2, Germany (Bonn) Ref. 2, Spain (Barcelona) Ref. 1, 2014, UK (NIA-UK) Ref. 1, 2014, USA (Cache County) Ref. 1, 2014, USA (Knight-ADRC) Ref. 1, 2014, USA (NIA-LOAD)
1.08 1.84 0.76 1.33 1.01 2.30 1.77 2.43 2.43
(0.59, 1.96) (0.64, 5.28) (0.55, 1.05) (0.78, 2.26) (0.72, 1.41) (0.88, 6.01) (0.86, 3.65) (1.25, 4.72) (1.38, 4.26)
0.4 0.6
1.0
2.0
4.0 6.0 10.0
2.0
3.0
I2 65 21 0
0.6
0.8 1.0
4.0 5.0
Figure 1 | Forest plots of study-specific odds ratios of case–control data sets assessing the potential association between Alzheimer’s disease risk and Val232Met (rs145999145) (a) or Ala442Ala (rs4819) (b). Note that the metaanalysis results after stratification for the ‘initial data sets’ for both variants are slightly different from the summary results originally reported1 owing to different analysis procedures (the original summary results can be reproduced by pooling genotype counts across all included data sets and determining the odds ratio and P value from the resulting 2 3 2 table of Alzheimer’s disease cases and controls assuming a dominant model). Note that none of the data sets included in the meta-analyses contains overlapping samples. For the purpose of inclusion in this meta-analysis the two Barcelona data sets were combined to one data set; for more details on these samples see Heilmann et al.2.
all currently available case–control data sets (that is, after combining those from the three Comments2–4 with the data published by Cruchaga et al.1) are nominally significant, the statistical support of these results is weakened when compared to the original report1 (Val232Met, P 5 3.47 3 1024; Ala442Ala, P 5 0.0431; Fig. 1). Collectively, the findings from our study and those from several additional independent case– control data sets2–4 suggest that Val232Met, Ala442Ala or other rare variants at MAF ,0.05 in PLD3 do not have a major impact on Alzheimer’s disease risk beyond the initial report1. Likewise, a recent metaanalysis of genome-wide association study (GWAS) data from a large
Table 1 | Family-based association results for rare PLD3 variants and Alzheimer’s disease WGS variants
Val232Met (rs145999145) Ala442Ala (rs4819) Val232Met and Ala442Ala WGS variants, MAF ,0.01 WGS variants, MAF ,0.05 WGS coding variants WGS non-synonymous substitution
No. variants
Average MAF
No. informative families
Z
FBAT P
1 1 2 333 356 30 10
0.237 2.133 1.184 0.127 0.279 0.018 0.0011
5 14 14 21 46 203 5
22.304 0.281 21.279 0.817 1.23 0.629 21.917
0.0212 0.7785 0.201 0.4141 0.2187 0.5295 0.0527
WGS variants indicates DNA sequence variants derived from whole genome sequencing data from the NIMH AD Initiative study families6. MAF, minor allele frequency (in %; based on 1 randomly drawn unaffected individual per family); all test statistics were computed after including sex, age (that is, onset age in Alzheimer’s disease, age at last examination in unaffected individuals) and APOE e4 allele carrier status as covariates. Z, Z-score of the test statistic (negative scores indicate under-transmission of minor allele to affected individuals). FBAT P 5 P value derived from family-based association testing. No. informative families indicates the number of informative families contributing to the test statistic. Note that Cruchaga et al.1 had reported four Val232Met minor allele carriers in the NIMH families used in this study (that is, NH4-II.53, NH6-II.98, NH7-II.99, NH8-II.05 in Appendix Fig. 1). Using both WGS and Sanger sequencing, we were unable to confirm the presence of the Val232Met minor allele in two of these individuals (NH7-II.99 and NH8-II.05).
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BRIEF COMMUNICATIONS ARISING collection of independent case–control data sets had already excluded common variants (MAF .0.01) in or around PLD3 from showing any suggestive (that is, no SNP exhibited P # 0.001) evidence of association with Alzheimer’s disease in .54,000 individuals (see ref. 5 and the Comment by Lambert et al.3). In conclusion, analysis of WGS data in multiplex Alzheimer’s disease families from the NIMH data set revealed no noteworthy association between rare variants in PLD3 and Alzheimer’s disease risk. In fact, for the lead signal (Val232Met) in Cruchaga et al.1, we observed an effect opposite to that originally reported. Our negative data are in agreement with similarly negative results in almost 26,000 independent predominately sporadic Alzheimer’s disease cases and controls and with recent GWAS meta-analysis results excluding noteworthy effects of common PLD3 variants on Alzheimer’s disease risk5. Additional data will be required to assess further the proposed role, if any, of rare variants in PLD3 on Alzheimer’s disease risk.
Methods Genotypes were determined from Illumina short-read whole-genome sequencing using Freebayes8 variant calling (manuscript in preparation), and confirmed by Sanger sequencing; only confirmed carriers of Val232Met and Ala442Ala were considered for analysis. Data were analysed in single-variant and combined-variant (‘burden’) testing using the family-based association test software (FBAT v2.0.4)9,10. None of the NIMH families analysed carried known Alzheimer’s-disease-causing mutations in APP, PSEN1 and PSEN2 or pathological expansions at C9orf72. In addition, we performed fixed-effect meta-analyses combining case–control results from the original study and all three accompanying Comments2–4 as described here11. For the latter, age-adjusted ORs were used where available. Basavaraj V. Hooli1*, Christina M. Lill2,3,4*, Kristina Mullin1, Dandi Qiao5, Christoph Lange5, Lars Bertram2,4,6 & Rudolph E. Tanzi1 1 MassGeneral Institute for Neurodegenerative Diseases, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. email: [email protected] 2 Platform for Genome Analytics, Institutes of Neurogenetics & Integrative and Experimental Genomics, University of Lu¨beck, 23552 Lu¨beck, Germany. email: [email protected]
3
Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany. 4 Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. 5 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. 6 School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London W6 8RP, UK. * These authors contributed equally to this work. Received 15 July; accepted 16 October 2014. 1.
Cruchaga, C. et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease. Nature 505, 550–554 (2014). 2. Heilmann, S. et al. PLD3 in non-familial Alzheimer’s disease. Nature 520, http://dx.doi.org/10.1038/nature14039 (2015). 3. Lambert, J.-C. et al. PLD3 and sporadic Alzheimer’s disease risk. Nature 520, http://dx.doi.org/10.1038/nature14036 (2015). 4. van der Lee, S. J. et al. PLD3 variants in population studies. Nature 520, http://dx.doi.org/10.1038/nature14038 (2015). 5. Lambert, J. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nature Genet. 45, 1452–1458 (2013). 6. Blacker, D. et al. Results of a high-resolution genome screen of 437 Alzheimer’s disease families. Hum. Mol. Genet. 12, 23–32 (2003). 7. De, G., Yip, W. K., Ionita-Laza, I. & Laird, N. Rare variant analysis for family-based design. PLoS ONE 8, e48495 (2013). 8. Cantarel, B. L. et al. BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity. BMC Bioinform. 15, 104 (2014). 9. Laird, N. M., Horvath, S. & Xu, X. Implementing a unified approach to family-based tests of association. Genet. Epidemiol. 19 (suppl. 1), S36–S42 (2000). 10. Won, S. et al. On the analysis of genome-wide association studies in family-based designs: a universal, robust analysis approach and an application to four genomewide association studies. PLoS Genet. 5, e1000741 (2009). 11. Lill, C. M. et al. Comprehensive research synopsis and systematic meta-analyses in Parkinson’s disease genetics: The PDGene database. PLoS Genet. 8, e1002548 (2012). Author Contributions R.E.T., L.B., B.V.H. and C.M.L. designed the study; B.V.H. and K.M. generated data; C.M.L., D.Q. and C.L. performed statistical analyses; B.V.H., L.B., C.M.L. and R.E.T. wrote the paper. Competing Financial Interests Declared none. doi:10.1038/nature14040
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BRIEF COMMUNICATIONS ARISING Appendix The Appendix section contains Appendix Figure 1.
Appendix Figure 1 | Pedigree charts of all NIMH families with at least one carrier of the PLD3 Val232Met minor allele. Probands are indicated by arrows. Phenotype information for each individual from top to bottom are: black diamonds, Alzheimer’s disease; white diamonds, no Alzheimer’s disease at last clinical examination; ?, no DNA or clinical information available; age at onset (in affected individuals) or age at last examination (unaffected
individuals); APOE e4 genotype, PLD3 Val232Met carrier status (1 or 2). Note that individuals NH4-II.53, NH6-II.98, NH7-II.99, NH8-II.05 were reported to carry the PLD3 V232M minor allele in Cruchaga et al.1; despite multiple attempts, we were unable to confirm this finding in individuals NH7-II.99 and NH8-II.05.
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BRIEF COMMUNICATIONS ARISING Cruchaga & Goate reply REPLYING TO
B. V. Hooli et al. Nature 520, http://dx.doi.org/10.1038/nature14040 (2015)
In an accompanying Comment addressing our recent study1, Hooli et al.2 report a failure to replicate an association between the PLD3 Val232Met variant and Alzheimer’s disease using a family-based design. They analysed 439 late-onset Alzheimer’s disease families from the NIMH data set. Unfortunately, because the authors only report a P value and Z statistic it is difficult to interpret the result. The variant is present in 5 out of 439 families and shows a P 5 0.02, but is apparently over-transmitted to unaffected individuals. However, it is unclear how old these unaffected individuals are relative to affected individuals in these pedigrees or whether the Met 232 allele was present in the affected parent. Although the variant segregated perfectly in our initial families, an odds ratio (OR) of two in sporadic cases indicates that this variant will not show perfect segregation with disease in most families, as is the case for APOE4. Furthermore, it has been reported that even known pathogenic variants do not always segregate with disease status in late-onset families due to the presence of pre-symptomatic individuals and phenocopies3–6. Although these families may be enriched for genetic risk factors (see below), it is not clear whether this data set has enough power for lowfrequency and rare variant analyses. Recently, Bertram and colleagues published a study using this data set and others in which TREM2 was marginally significant with a very low OR7. The authors did not report the OR or the P value for TREM2 in the NIMH families alone. Disclosing the P value and OR for the NIMH families would be useful for comparison purposes, and to estimate the real power of this data set. Additionally, we are surprised to see such a large number of PLD3 variants in a small number of families: 333 (MAF ,0.05) and 356 (MAF ,0.01) variants were found in just 21 and 46 families, respectively. We are also surprised by the fact that 10 different variants were found in just 5 families, indicating that on average those families have 2 nonsynonymous variants in PLD3. In our sequencing data4 (4,000 samples) we did not find any individual with more than one non-synonymous variant in PLD3. It is unclear whether the same individuals carried more than one variant in these families or whether different individuals within the same family carried different variants. Hooli et al.2 also report coding variants in 203 of the 439 families: or in 46% of the families. In our study
we found coding variants in just 7.99% of the cases and 3.06% of the controls. Based on these data, when the frequency of coding variants in the Alzheimer’s disease families is compared with healthy unrelated controls, it would yield an OR 5 15.7 (11.5–21.3) and a P value of P 5 1.35 3 10286, which would strongly support the role of PLD3 in Alzheimer’s disease. On the basis of the huge difference in the numbers of nonsynonymous variants in these families compared to both our own sequencing and the exome Variant Server data (http://evs.gs.washington. edu/EVS/), the calling in this gene region in these samples appears to be highly divergent, raising the question of whether these results are reliable. C. Cruchaga and A. M. Goate prepared this Reply on behalf of all authors of ref. 1. Carlos Cruchaga1,2 & Alison M. Goate1,2 1 Department of Psychiatry, Washington University, St Louis, Missouri 63110, USA. email: [email protected] 2 Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St Louis, Missouri 63110, USA. 1. 2. 3.
4. 5.
6.
7.
Cruchaga, C. et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease. Nature 505, 550–554 (2014). Hooli, B. V. et al. PLD3 gene variants and Alzheimer’s disease. Nature 520, http://dx.doi.org/10.1038/nature14040 (2015). Kauwe, J. S. et al. Extreme cerebrospinal fluid amyloid beta levels identify family with late-onset Alzheimer’s disease presenilin 1 mutation. Ann. Neurol. 61, 446–453 (2007). Cruchaga, C. et al. Rare variants in APP, PSEN1 and PSEN2 increase risk for AD in late-onset Alzheimer’s disease families. PLoS ONE 7, e31039 (2012). Rossor, M. N., Fox, N. C., Beck, J., Campbell, T. C. & Collinge, J. Incomplete penetrance of familial Alzheimer’s disease in a pedigree with a novel presenilin-1 gene mutation. Lancet 347, 1560 (1996). Llado, A. et al. A novel PSEN1 mutation (K239N) associated with Alzheimer’s disease with wide range age of onset and slow progression. Eur. J. Neurol. 17, 994–996 (2010). Bertram, L., Parrado, A. R. & Tanzi, R. E. TREM2 and neurodegenerative disease. N. Engl. J. Med. 369, 1565 (2013).
doi:10.1038/nature14041
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C. Cruchaga et al. Nature 505, 550–554 (2014); doi:10.1038/nature12825
Cruchaga et al. recently reported1 evidence for genetic association between Alzheimer’s disease risk and several rare DNA sequence variants in the phospholipase D3 gene (PLD3). The study’s lead signal Val232Met (rs145999145) co-segregated with Alzheimer’s disease in multiple affected families, and also showed association with Alzheimer’s disease risk in case–control samples; whereas two other highly conserved PLD3 variants, Ala442Ala (rs4819) and Met6Arg, showed nominal association with disease risk. Our efforts to replicate these findings in a large collection of family-based Alzheimer’s disease data failed to reveal any risk effect of PLD3 in Alzheimer’s disease. Our negative results, taken together with equally negative companion reports2–4 and recent GWAS meta-analysis results5, call for additional studies to examine the proposed role, if any, of rare variants in PLD3 on Alzheimer’s disease risk. There is a Reply to this Brief Communication Arising by Cruchaga, C. & Goate, A. M. Nature 520, http://dx.doi.org/10.1038/ nature14041 (2015). We tested all three of the previously reported PLD3 variants for association with Alzheimer’s disease in the National Institute of Mental Health Alzheimer’s Genetics Initiative Study Sample (NIMH, 439 multiplex families comprising 1,440 subjects; average onset age of patients: 72.4 6 7.7 years (s.d.))6. All tested NIMH subjects were monomorphic for the major allele of Met6Arg. While we observed a nominally significant signal for Val232Met in our analyses (P 5 0.0212, Table 1), this was due to over-transmission of the presumed risk allele to unaffected individuals in the NIMH data set (Appendix Fig. 1). This is in direct contrast to the data reported by Cruchaga et al.1, where the minor methionine (Met) allele was reported as conferring increased risk. The other proposed PLD3 risk variant, Ala442Ala, exhibited no association with risk for Alzheimer’s disease in the NIMH data set (P 5 0.779). Burden testing7 (weighted by minor allele frequency (MAF)) using all the PLD3 variants from the WGS data with MAF ,0.01 (333 variants) and ,0.05 (356 variants) did not reveal significant association with Alzheimer’s disease. Limiting the burden analyses to coding region (n 5 30) and non-synonymous coding region (n 5 10) variants also failed to show association with the disease (P 5 0.53 and 0.053; Table 1). Our nonsignificant results are in line with largely negative findings from three Comments (Heilmann et al.2, Lambert et al.3 and van der Lee et al.4) reporting on independent association data for both variants. Along these lines, fixed-effect meta-analyses across the effect estimates reported in these three Comments do not show nominally significant association with either variant: odds ratio (OR)Val232Met 5 1.29 (95% confidence interval (CI) 0.93–1.79), P 5 0.132 across 7,565 cases and 18,424 controls; ORAla442Ala 5 0.97 (95% CI 0.79–1.18), P 5 0.752 across 6,679 cases and 11,911 controls (Fig. 1). Finally, while meta-analyses across
a All data sets Validation data sets Initial data sets
OR 1.62 1.29 2.44
95% Cl (1.24, 2.10) (0.93, 1.79) (1.57, 3.79)
Data-set-specific ORs Ref. 4, Iceland (AGES) Ref. 4, Netherlands (Dutch AD centres) Ref. 4, Netherlands (GRIP) Ref. 4, Netherlands (RS) Ref. 4, USA (ADNI) Ref. 4, USA (FHS) Ref. 3, France Ref. 2, Germany (Bonn) Ref. 2 Spain (Barcelona) Ref. 1, 2014, Canada (Toronto) Ref. 1, 2014, UK (Nottingham) Ref. 1, 2014, USA (Cache County) Ref. 1, 2014, USA (Knight-ADRC) Ref. 1, 2014, USA (NIA-LOAD) Ref. 1, 2014, USA (Pittsburgh)
3.18 1.55 1.58 1.43 2.94 2.63 1.17 0.49 1.23 4.71 1.05 2.03 6.63 3.09 1.82
(0.17, 58.73) (0.25, 9.38) (0.25, 9.91) (0.51, 4.03) (0.63, 13.80) (0.71, 9.70) (0.67, 2.04) (0.15, 1.65) (0.67, 2.26) (0.54, 40.89) (0.26, 4.25) (0.83, 4.95) (1.52, 28.91) (1.41, 6.79) (0.70, 4.73)
I2 6 0 0
0.2
b All data sets Validation data sets Initial data sets
OR 1.19 0.97 2.25
95% Cl (1.01, 1.42) (0.79, 1.18) (1.59, 3.17)
Data-set-specific ORs Ref. 4, Netherlands (Dutch AD centres) Ref. 4, USA (ADNI) Ref. 3, France Ref. 2, Germany (Bonn) Ref. 2, Spain (Barcelona) Ref. 1, 2014, UK (NIA-UK) Ref. 1, 2014, USA (Cache County) Ref. 1, 2014, USA (Knight-ADRC) Ref. 1, 2014, USA (NIA-LOAD)
1.08 1.84 0.76 1.33 1.01 2.30 1.77 2.43 2.43
(0.59, 1.96) (0.64, 5.28) (0.55, 1.05) (0.78, 2.26) (0.72, 1.41) (0.88, 6.01) (0.86, 3.65) (1.25, 4.72) (1.38, 4.26)
0.4 0.6
1.0
2.0
4.0 6.0 10.0
2.0
3.0
I2 65 21 0
0.6
0.8 1.0
4.0 5.0
Figure 1 | Forest plots of study-specific odds ratios of case–control data sets assessing the potential association between Alzheimer’s disease risk and Val232Met (rs145999145) (a) or Ala442Ala (rs4819) (b). Note that the metaanalysis results after stratification for the ‘initial data sets’ for both variants are slightly different from the summary results originally reported1 owing to different analysis procedures (the original summary results can be reproduced by pooling genotype counts across all included data sets and determining the odds ratio and P value from the resulting 2 3 2 table of Alzheimer’s disease cases and controls assuming a dominant model). Note that none of the data sets included in the meta-analyses contains overlapping samples. For the purpose of inclusion in this meta-analysis the two Barcelona data sets were combined to one data set; for more details on these samples see Heilmann et al.2.
all currently available case–control data sets (that is, after combining those from the three Comments2–4 with the data published by Cruchaga et al.1) are nominally significant, the statistical support of these results is weakened when compared to the original report1 (Val232Met, P 5 3.47 3 1024; Ala442Ala, P 5 0.0431; Fig. 1). Collectively, the findings from our study and those from several additional independent case– control data sets2–4 suggest that Val232Met, Ala442Ala or other rare variants at MAF ,0.05 in PLD3 do not have a major impact on Alzheimer’s disease risk beyond the initial report1. Likewise, a recent metaanalysis of genome-wide association study (GWAS) data from a large
Table 1 | Family-based association results for rare PLD3 variants and Alzheimer’s disease WGS variants
Val232Met (rs145999145) Ala442Ala (rs4819) Val232Met and Ala442Ala WGS variants, MAF ,0.01 WGS variants, MAF ,0.05 WGS coding variants WGS non-synonymous substitution
No. variants
Average MAF
No. informative families
Z
FBAT P
1 1 2 333 356 30 10
0.237 2.133 1.184 0.127 0.279 0.018 0.0011
5 14 14 21 46 203 5
22.304 0.281 21.279 0.817 1.23 0.629 21.917
0.0212 0.7785 0.201 0.4141 0.2187 0.5295 0.0527
WGS variants indicates DNA sequence variants derived from whole genome sequencing data from the NIMH AD Initiative study families6. MAF, minor allele frequency (in %; based on 1 randomly drawn unaffected individual per family); all test statistics were computed after including sex, age (that is, onset age in Alzheimer’s disease, age at last examination in unaffected individuals) and APOE e4 allele carrier status as covariates. Z, Z-score of the test statistic (negative scores indicate under-transmission of minor allele to affected individuals). FBAT P 5 P value derived from family-based association testing. No. informative families indicates the number of informative families contributing to the test statistic. Note that Cruchaga et al.1 had reported four Val232Met minor allele carriers in the NIMH families used in this study (that is, NH4-II.53, NH6-II.98, NH7-II.99, NH8-II.05 in Appendix Fig. 1). Using both WGS and Sanger sequencing, we were unable to confirm the presence of the Val232Met minor allele in two of these individuals (NH7-II.99 and NH8-II.05).
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BRIEF COMMUNICATIONS ARISING collection of independent case–control data sets had already excluded common variants (MAF .0.01) in or around PLD3 from showing any suggestive (that is, no SNP exhibited P # 0.001) evidence of association with Alzheimer’s disease in .54,000 individuals (see ref. 5 and the Comment by Lambert et al.3). In conclusion, analysis of WGS data in multiplex Alzheimer’s disease families from the NIMH data set revealed no noteworthy association between rare variants in PLD3 and Alzheimer’s disease risk. In fact, for the lead signal (Val232Met) in Cruchaga et al.1, we observed an effect opposite to that originally reported. Our negative data are in agreement with similarly negative results in almost 26,000 independent predominately sporadic Alzheimer’s disease cases and controls and with recent GWAS meta-analysis results excluding noteworthy effects of common PLD3 variants on Alzheimer’s disease risk5. Additional data will be required to assess further the proposed role, if any, of rare variants in PLD3 on Alzheimer’s disease risk.
Methods Genotypes were determined from Illumina short-read whole-genome sequencing using Freebayes8 variant calling (manuscript in preparation), and confirmed by Sanger sequencing; only confirmed carriers of Val232Met and Ala442Ala were considered for analysis. Data were analysed in single-variant and combined-variant (‘burden’) testing using the family-based association test software (FBAT v2.0.4)9,10. None of the NIMH families analysed carried known Alzheimer’s-disease-causing mutations in APP, PSEN1 and PSEN2 or pathological expansions at C9orf72. In addition, we performed fixed-effect meta-analyses combining case–control results from the original study and all three accompanying Comments2–4 as described here11. For the latter, age-adjusted ORs were used where available. Basavaraj V. Hooli1*, Christina M. Lill2,3,4*, Kristina Mullin1, Dandi Qiao5, Christoph Lange5, Lars Bertram2,4,6 & Rudolph E. Tanzi1 1 MassGeneral Institute for Neurodegenerative Diseases, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. email: [email protected] 2 Platform for Genome Analytics, Institutes of Neurogenetics & Integrative and Experimental Genomics, University of Lu¨beck, 23552 Lu¨beck, Germany. email: [email protected]
3
Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany. 4 Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. 5 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. 6 School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London W6 8RP, UK. * These authors contributed equally to this work. Received 15 July; accepted 16 October 2014. 1.
Cruchaga, C. et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease. Nature 505, 550–554 (2014). 2. Heilmann, S. et al. PLD3 in non-familial Alzheimer’s disease. Nature 520, http://dx.doi.org/10.1038/nature14039 (2015). 3. Lambert, J.-C. et al. PLD3 and sporadic Alzheimer’s disease risk. Nature 520, http://dx.doi.org/10.1038/nature14036 (2015). 4. van der Lee, S. J. et al. PLD3 variants in population studies. Nature 520, http://dx.doi.org/10.1038/nature14038 (2015). 5. Lambert, J. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nature Genet. 45, 1452–1458 (2013). 6. Blacker, D. et al. Results of a high-resolution genome screen of 437 Alzheimer’s disease families. Hum. Mol. Genet. 12, 23–32 (2003). 7. De, G., Yip, W. K., Ionita-Laza, I. & Laird, N. Rare variant analysis for family-based design. PLoS ONE 8, e48495 (2013). 8. Cantarel, B. L. et al. BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity. BMC Bioinform. 15, 104 (2014). 9. Laird, N. M., Horvath, S. & Xu, X. Implementing a unified approach to family-based tests of association. Genet. Epidemiol. 19 (suppl. 1), S36–S42 (2000). 10. Won, S. et al. On the analysis of genome-wide association studies in family-based designs: a universal, robust analysis approach and an application to four genomewide association studies. PLoS Genet. 5, e1000741 (2009). 11. Lill, C. M. et al. Comprehensive research synopsis and systematic meta-analyses in Parkinson’s disease genetics: The PDGene database. PLoS Genet. 8, e1002548 (2012). Author Contributions R.E.T., L.B., B.V.H. and C.M.L. designed the study; B.V.H. and K.M. generated data; C.M.L., D.Q. and C.L. performed statistical analyses; B.V.H., L.B., C.M.L. and R.E.T. wrote the paper. Competing Financial Interests Declared none. doi:10.1038/nature14040
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BRIEF COMMUNICATIONS ARISING Appendix The Appendix section contains Appendix Figure 1.
Appendix Figure 1 | Pedigree charts of all NIMH families with at least one carrier of the PLD3 Val232Met minor allele. Probands are indicated by arrows. Phenotype information for each individual from top to bottom are: black diamonds, Alzheimer’s disease; white diamonds, no Alzheimer’s disease at last clinical examination; ?, no DNA or clinical information available; age at onset (in affected individuals) or age at last examination (unaffected
individuals); APOE e4 genotype, PLD3 Val232Met carrier status (1 or 2). Note that individuals NH4-II.53, NH6-II.98, NH7-II.99, NH8-II.05 were reported to carry the PLD3 V232M minor allele in Cruchaga et al.1; despite multiple attempts, we were unable to confirm this finding in individuals NH7-II.99 and NH8-II.05.
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BRIEF COMMUNICATIONS ARISING Cruchaga & Goate reply REPLYING TO
B. V. Hooli et al. Nature 520, http://dx.doi.org/10.1038/nature14040 (2015)
In an accompanying Comment addressing our recent study1, Hooli et al.2 report a failure to replicate an association between the PLD3 Val232Met variant and Alzheimer’s disease using a family-based design. They analysed 439 late-onset Alzheimer’s disease families from the NIMH data set. Unfortunately, because the authors only report a P value and Z statistic it is difficult to interpret the result. The variant is present in 5 out of 439 families and shows a P 5 0.02, but is apparently over-transmitted to unaffected individuals. However, it is unclear how old these unaffected individuals are relative to affected individuals in these pedigrees or whether the Met 232 allele was present in the affected parent. Although the variant segregated perfectly in our initial families, an odds ratio (OR) of two in sporadic cases indicates that this variant will not show perfect segregation with disease in most families, as is the case for APOE4. Furthermore, it has been reported that even known pathogenic variants do not always segregate with disease status in late-onset families due to the presence of pre-symptomatic individuals and phenocopies3–6. Although these families may be enriched for genetic risk factors (see below), it is not clear whether this data set has enough power for lowfrequency and rare variant analyses. Recently, Bertram and colleagues published a study using this data set and others in which TREM2 was marginally significant with a very low OR7. The authors did not report the OR or the P value for TREM2 in the NIMH families alone. Disclosing the P value and OR for the NIMH families would be useful for comparison purposes, and to estimate the real power of this data set. Additionally, we are surprised to see such a large number of PLD3 variants in a small number of families: 333 (MAF ,0.05) and 356 (MAF ,0.01) variants were found in just 21 and 46 families, respectively. We are also surprised by the fact that 10 different variants were found in just 5 families, indicating that on average those families have 2 nonsynonymous variants in PLD3. In our sequencing data4 (4,000 samples) we did not find any individual with more than one non-synonymous variant in PLD3. It is unclear whether the same individuals carried more than one variant in these families or whether different individuals within the same family carried different variants. Hooli et al.2 also report coding variants in 203 of the 439 families: or in 46% of the families. In our study
we found coding variants in just 7.99% of the cases and 3.06% of the controls. Based on these data, when the frequency of coding variants in the Alzheimer’s disease families is compared with healthy unrelated controls, it would yield an OR 5 15.7 (11.5–21.3) and a P value of P 5 1.35 3 10286, which would strongly support the role of PLD3 in Alzheimer’s disease. On the basis of the huge difference in the numbers of nonsynonymous variants in these families compared to both our own sequencing and the exome Variant Server data (http://evs.gs.washington. edu/EVS/), the calling in this gene region in these samples appears to be highly divergent, raising the question of whether these results are reliable. C. Cruchaga and A. M. Goate prepared this Reply on behalf of all authors of ref. 1. Carlos Cruchaga1,2 & Alison M. Goate1,2 1 Department of Psychiatry, Washington University, St Louis, Missouri 63110, USA. email: [email protected] 2 Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St Louis, Missouri 63110, USA. 1. 2. 3.
4. 5.
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7.
Cruchaga, C. et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer’s disease. Nature 505, 550–554 (2014). Hooli, B. V. et al. PLD3 gene variants and Alzheimer’s disease. Nature 520, http://dx.doi.org/10.1038/nature14040 (2015). Kauwe, J. S. et al. Extreme cerebrospinal fluid amyloid beta levels identify family with late-onset Alzheimer’s disease presenilin 1 mutation. Ann. Neurol. 61, 446–453 (2007). Cruchaga, C. et al. Rare variants in APP, PSEN1 and PSEN2 increase risk for AD in late-onset Alzheimer’s disease families. PLoS ONE 7, e31039 (2012). Rossor, M. N., Fox, N. C., Beck, J., Campbell, T. C. & Collinge, J. Incomplete penetrance of familial Alzheimer’s disease in a pedigree with a novel presenilin-1 gene mutation. Lancet 347, 1560 (1996). Llado, A. et al. A novel PSEN1 mutation (K239N) associated with Alzheimer’s disease with wide range age of onset and slow progression. Eur. J. Neurol. 17, 994–996 (2010). Bertram, L., Parrado, A. R. & Tanzi, R. E. TREM2 and neurodegenerative disease. N. Engl. J. Med. 369, 1565 (2013).
doi:10.1038/nature14041
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