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Rare coding variants in PLCG2, ABI3, and TREM2
implicate microglial-mediated innate immunity in
Alzheimer's disease.
Rebecca Sims
Sven J van der Lee
Adam C Naj
Céline Bellenguez
Nandini Badarinarayan
See next page for additional authors
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Rare coding variants in PLCG2, ABI3 and TREM2 implicate
microglial-mediated innate immunity in Alzheimer’s disease
A full list of authors and affiliations appears at the end of the article.
Introduction
We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-
control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome
microarray. In stage 2, we tested associated variants (
P
<1×10
-4
) in 35,962 independent samples
using
de novo
genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were
used to test the most significant stage 2 associations (
P
<5×10
-8
) using imputed genotypes. We
observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a
protective variant in
PLCG2
(rs72824905/p.P522R,
P
=5.38×10
-10
, OR=0.68, MAF
cases
=0.0059,
MAF
controls
=0.0093), a risk variant in
ABI3
(rs616338/p.S209F,
P
=4.56×10
-10
, OR=1.43,
MAF
cases
=0.011, MAF
controls
=0.008), and a novel GWS variant in
TREM2
(rs143332484/
p.R62H,
P
=1.55×10
-14
, OR=1.67, MAF
cases
=0.0143, MAF
controls
=0.0089), a known AD
susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and
highlight an immune-related protein-protein interaction network enriched for previously identified
AD risk genes. These genetic findings provide additional evidence that the microglia-mediated
innate immune response contributes directly to AD development.
Late-onset AD (LOAD) has a significant genetic component (
h
2
=58-79%
1
). Nearly 30
LOAD susceptibility loci
2-12
are known, and risk is significantly polygenic
13
. However,
these loci explain only a proportion of disease heritability. Rare variants also contribute to
disease risk
14-17
. Recent sequencing studies identified a number of genes that have rare
variants associated with AD
9-11,18-24
. Our approach to rare-variant discovery is to genotype
a large sample with micro-arrays targeting known exome variants with follow-up using
genotyping and imputed genotypes in a large independent sample. This is a cost-effective
alternative to
de novo
sequencing
25-29
.
~
corresponding author.
*
equal contribution first author
**
equal contribution senior author
Competing Financial Interests Statement
Robert R. Graham and Timothy W. Behrens are full-time employees of Genentech Inc. Deborah Blacker is a consultant for Biogen
Inc. Ronald C. Petersen is a consultant for Roche Inc., Merck Inc., Genentech Inc., Biogen Inc., and Eli Lilly. Ashley R. Winslow is a
former employee and stockholder of Pfizer, Inc., and a current employee of the Perelman School of Medicine at the University of
Pennsylvania Orphan Disease Center in partnership with the Loulou. Alison M. Goate is a member of the scientific advisory board for
Denali Therapeutics. Nilufer Ertekin-Taner is a consultant for Cytox. John Hardy holds a collaborative grant with Cytox cofunded by
Department of Business (Biz). Frank Jessen acts as a consultant for Novartis, Eli Lilly, Nutricia, MSD, Roche and Piramal. Neither Dr.
Morris nor his family owns stock or has equity interest (outside of mutual funds or other externally directed accounts) in any
pharmaceutical or biotechnology company. Dr. Morris is currently participating in clinical trials of antidementia drugs from Eli Lilly
and Company, Biogen, and Janssen. Dr. Morris serves as a consultant for Lilly USA. He receives research support from Eli Lilly/Avid
Radiopharmaceuticals and is funded by NIH grants # P50AG005681; P01AG003991; P01AG026276 and UF01AG032438.
HHS Public Access
Author manuscript
Nat Genet
. Author manuscript; available in PMC 2018 March 01.
Published in final edited form as:
Nat Genet
. 2017 September ; 49(9): 1373–1384. doi:10.1038/ng.3916.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
We applied a 3-stage design (Supplementary Figure 1) using subjects from the International
Genomics of Alzheimer’s Project (IGAP)(Table 1, Supplementary Tables 1 & 2). In stage 1,
16,097 LOAD cases and 18,077 cognitively normal elderly controls were genotyped using
the Illumina HumanExome microarray. Data from multiple consortia were combined in a
single variant meta-analysis (Online Methods) assuming an additive model. In total, 241,551
variants passed quality-control (Supplementary Table 3). Of these 203,902 were
polymorphic, 26,947 were common (minor allele frequency (MAF)≥5%), and 176,955 were
low frequency or rare (MAF<5%). We analyzed common variants using a logistic regression
model in each sample cohort and combined data using METAL
30
. Rare and low frequency
variants were analyzed using the score test and data combined with SeqMeta
31
(Supplementary Figure 2).
We reviewed cluster plots for variants showing association (
P
<1×10
-4
) and identified 43
candidate variants (Supplementary Table 4) exclusive of known risk loci (Supplementary
Table 5). Stage 2 tested these for association in 14,041 LOAD cases and 21,921 controls,
using
de novo
and imputation derived genotypes (Online Methods). We carried forward
single nucleotide variants (SNVs) with GWS associations and consistent directions of effect
to stage 3 where genotypes for 6,652 independent cases and 8,345 controls were imputed
using the Haplotype Reference Consortium resource
32,33
(Online Methods, Supplementary
Table 6).
We identified four rare coding variants with GWS association signals with LOAD
(
P
<5×10
-8
)(Table 2, Supplementary Tables 7 & 8). The first is a missense variant p.P522R
(
P
=5.38×10
-10
, OR=0.68) in
Phospholipase C Gamma 2
(
PLCG2
)(Table 2, Figure 1a,
Supplementary Table 9, Supplementary Figure 3). This variant is associated with decreased
risk of LOAD, showing a MAF of 0.0059 in cases and 0.0093 in controls. The reference
allele (p.P522) is conserved across several species (Supplementary Figure 4). Gene-wide
analysis showed nominal evidence for association at
P
=1.52×10
-4
(Supplementary Tables 10
& 11) and we found no other independent association at this gene (Supplementary Figure 5).
The second novel association is a missense change p.S209F (
P
=4.56×10
-10
, OR=1.43) in
B3
domain-containing transcription factor ABI3
(
ABI3
). The p.F209 variant shows consistent
evidence for increasing LOAD risk across all stages, with a MAF of 0.011 in cases and
0.008 in controls (Table 2, Figure 1b, Supplementary Table 12, Supplementary Figure 6).
The reference allele is conserved across multiple species (Supplementary Figure 7). Gene-
wide analysis showed nominal evidence of association (
P
=5.22×10
-5
)(Supplementary Tables
10 & 11). The
B4GALNT2
gene, adjacent to
ABI3
, contained an independent suggestive
association (Supplementary Figure 8), but this failed to replicate in subsequent stages
(
P
combined
=1.68×10
-4
)(Supplementary Table 7).
Following reports of suggestive association with LOAD
34,35
, we report the first evidence for
GWS association at
TREM2
coding variant p.R62H (
P
=1.55×10
-14
, OR=1.67), with a MAF
of 0.0143 in cases and 0.0089 in controls (Table 2, Figure 1c, Supplementary Table 13,
Supplementary Figures 9 & 10). We also observed evidence for the previously reported
9,11
TREM2
rare variant p.R47H (Table 2). These variants are not in linkage disequilibrium
(Supplementary Table 14) and conditional analyses confirmed that p.R62H and p.R47H are
Sims et al.
Page 2
Nat Genet
. Author manuscript; available in PMC 2018 March 01.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript