Role of genetics in progression through various stages of AMD
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progression to different stages of age-related macular degeneration
(AMD).
AMD is known to be influenced primarily by genetic factors, although
environmental and behavioral factors also play important roles.
Multiple studies have shown that several genes in the alternative
complement pathway (CFH, C2, CFB, C3, CFI) are associated with AMD.
This pathway and related mechanisms have been extensively studied in
relation to AMD, and is one of the major susceptibility factors. The
ARMS2/HTRA1 region is also strongly associated with AMD, although its
function is still not confirmed. More recently, genes in the high
density lipoprotein (HDL) cholesterol pathway (LIPC, ABCA1, CETP),
extracellular matrix pathway (TIMP3, COL10A1, COL8A1) and angiogenesis
pathway (VEGFA) have been shown to be associated with AMD in GWAS
studies.
Our case-control study of the association between these variants and
early, intermediate and late AMD suggested that genes in the
complement and the HDL pathways may have specific influences on
different stages of AMD. To our knowledge, no study has explored the
effect of these recently reported genetic loci on AMD progression from
normal to intermediate stages, and then to advanced stages in a
prospective study.
In order to assess the effect of genetic and other prognostic factors
on each stage of AMD and to apply genetic knowledge to assess its
impact on the natural history of the disease, we studied the
progression of AMD by combining the genetic, environmental and
demographic factors using Markov modeling. Multi-state Markov modeling
is designed for analyses that involve many disease stages. It can
estimate the effects of each factor on the risk of transition from one
disease stage to another, so that we are able to compare the effects
of each factor on progression to different AMD stages.
The aim of the present study is to further expand our previous studies
by the following: adding seven recently reported AMD genes to
progression analyses; incorporating transitions among 5-stages of AMD;
and applying a new statistical model to evaluate the different effects
of multiple genes on risk of progression to different stages of AMD.
Methods & Results
Progression event and time to each stage of AMD were derived from the
longitudinal data of 2560 subjects without advanced AMD. SNPs in 12
AMD risk loci were genotyped. A multi-state Markov model for
progression from normal to intermediate drusen, then to large drusen,
and eventually to neovascular disease (NV) or geographic atrophy (GA)
was applied to estimate stage-specific hazard ratios for each SNP. The
effects of these genetic factors were also estimated by a multivariate
multi-state Markov model adjusted for baseline age, gender, smoking,
body mass index (BMI), education, antioxidant treatment, and the
status of AMD in the fellow eye.
Controlling for demographic and behavioral factors and other SNPs, the
TT genotype of rs10468017 in LIPC was associated with decreased risk
of progression from large drusen to NV (HR=0.57, P=0.04) and tended to
reduce the risk of progression from normal to intermediate drusen
(HR=0.72, P=0.07). Rs1883025 (T allele) in ABCA1 was associated with
decreased risk of progression from normal to intermediate drusen (HR
per allele = 0.82 per allele, P=9.7x10(-3)) and from intermediate
drusen to large drusen (HR per allele =0.77, P=5.2x10(-3)). The genes
CFH, C3, CFB, and ARMS2/HTRA1 were associated with progression from
intermediate drusen to large drusen, and from large drusen to GA or
NV.
Discussion & Conclusions
This is the first study using a multi-state Markov model to evaluate
12 genetic variants, behavioral and demographic factors and
progression through 4 distinct stages of AMD. In this study we found
that several SNPs were associated with risk of progression through
multiple stages of AMD, while others were only associated with a
specific transition. A schematic diagram (FIGURE) shows the genetic
effects on different stages of AMD progression.
This hypothetical model suggests that HDL genes play important roles
in drusen initiation at the early stages of AMD, and then as drusen
accumulate between the RPE and Bruch's membrane, genes in the
complement pathway are activated.
These new findings of transition-specific genetic effects for AMD
progression may be helpful for designing treatment or prevention
strategies at specific stages of the disease. The 5-state model in
this study could be used to predict risk of progression to each AMD
stage at a given time for an individual with a given genetic and
clinical profile. This model could also be useful for making treatment
and follow-up decisions and counseling individual patients.
Only a few studies have investigated the possible role of genetic
variants in drusen accumulation and early stages of AMD. In our recent
study, genes in the HDL pathway were associated with early stages of
AMD, while ARMS2/HTRA1 and genes in the complement pathway were
associated with the advanced stages. The results of this multi-state
analysis for progression are consistent with our previous findings
based on association studies and show that three major risk genes CFH,
ARMS2/HTRA1 and C3 increase risk of progression from intermediate
drusen to large drusen and from large drusen to GA and NV.
The Markov model suggests that the result of ABCA1 in the case-control
analysis may be driven by the effect of rs1883025 on decreasing risk
of progression in the early stages of AMD (normal to intermediate
drusen and from intermediate drusen to large drusen). The C allele of
COL8A1 appeared to increase the risk of progression to the advanced
stages, which is significant in the univariate analysis. However the C
allele seems to be protective for the transition from intermediate to
large drusen.
In the multi-state Markov model which included demographic,
environmental, and ocular variables, these results suggest that BMI
>30 significantly increases the risk of progression from large drusen
to GA. It is possible that GA and high BMI are both pleiotropic
phenotypes related to dysfunction of lipid metabolism. This study also
confirmed previous reports that smoking behavior, particularly current
smoking, could strongly increase the risk of progression to advanced
AMD. Quitting smoking is probably the most effective life style change
for patients to reduce their risk of advanced AMD. It has been known
that eyes of patients with early or late AMD are often symmetrical.
The ocular status of the fellow eye of patients was highly predictive
of progression events for each transition.
Combining demographic, behavioral and ocular information together with
genetic factors, the multi-state model could help us to estimate the
probability of disease progression. Individuals with high risk profile
were predicted to be much more likely to be in the advanced stages
than individuals with the low risk profile. This is the first risk
prediction model that provides quantitative estimation of
probabilities in 5 different AMD stages for a patient with a given
risk profile. If applied in clinical practice, it may help clinicians
to determine the frequency of eye exams and help to make treatment
plans for patients according to their risk profile.
In summary, these results suggest that genes associated with AMD may
be involved in transitions between different AMD stages during
progression. Complement genes play important roles in the progression
from intermediate drusen to large drusen and from large drusen to the
advanced AMD stages. We also identified a novel association between
ABCA1 in the HDL pathway and reduced risk of progression from normal
to intermediate drusen and from intermediate drusen to large drusen.
Functional studies are needed to investigate the roles of the HDL
pathway genes in the early stages of AMD. The multi-state Markov model
is a powerful tool to identify novel genetic variants influencing
progression in early stages of AMD and adds new insights into the
mechanisms and etiology of this disease.
Invest Ophthalmol Vis Sci. 2012 Jan 12. [Epub ahead of print]
http://www.ncbi.nlm.nih.gov/pubmed/22247473
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