Postmortem human donor eyes were obtained from the Utah Lions Eye Bank (Salt Lake City, UT, USA). They were selected from 1601 donors with a date of death between May 2010 and May 2014. In all cases prior consent had been obtained for the ocular tissue to be used for research, and the research adhered to the tenets of the Declaration of Helsinki. The eyes were fixed in 4% (vol/vol) paraformaldehyde, within 4 hours post mortem, for 2 hours at 4°C, then stored in sodium cacodylate buffer at 4°C. Medical and ophthalmic histories (including information on tobacco/smoking history), a family questionnaire, blood, and sera were obtained from most donors (and all donors used in this study). Eyes were classified by using standardized fundal photography and AMD grading criteria, as previously described.²⁸ 

DNA was extracted from whole blood by using the QIAamp DNA Blood Maxi Kit (Qiagen, Valencia, CA, USA). Single nucleotide polymorphism (SNP) genotypes were then determined by using the TaqMan platform (Applied Biosystems [ABI], Waltham, MA, USA) under the manufacturer's recommended conditions. All SNP assays were predesigned with the exception of rs1061170, which was made by using ABI's Custom TaqMan Assay Design Tool. Samples were amplified by using a PTC-225 Thermal Cycler (Madison James Research, Asheboro, NC, USA) and analyzed on the Applied Biosystems 7900HT Fast Real-Time PCR System. 

Donor eyes were selected and stratified into groups by diplotype at the AMD-associated CFH-to-F13B locus (Table 1), including homozygous risk diplotype, homozygous neutral diplotype, and homozygous protective diplotype. Importantly, all donors were homozygous nonrisk at the ARMS2/HTRA1 locus on chromosome 10. Diplotype assignment was made on the basis of eight tagging SNPs within the CFH-to-F13B locus (Table 2), as previous research²³ has demonstrated that these provide the most parsimonious combination of SNPs for allocation of donors into five common haplotypes. 

Age-related macular degeneration was not an inclusion or exclusion criterion and tissue selection was made blind to the presence or absence of AMD, either through positive clinical history or the presence of postmortem evidence of AMD before tissue sectioning. This information was revealed after image analysis and it transpired that none of the study donors had a clinical diagnosis of AMD or were found to have AMD by standardized grading of the postmortem tissue. Aside from AMD genotype, inclusion criteria for the donors were Caucasian race, age between 55 and 79 years (i.e., aiming for predominantly preclinical phase of disease; see Discussion), and a complete and verified medical and ophthalmic history. Donors were excluded from the study if they had a past history of glaucoma, diabetic retinopathy, retinal vascular occlusion, or retinal detachment. In addition, the presence of hepatic disease was used as an exclusion criterion, as this could influence CFH levels. 

From genetic analyses of the 1601 donors, and applying the inclusion/exclusion criteria, 24 risk, 2 neutral, and 7 protective diplotype donors with no risk variants at ARMS2/HTRA1 were identified. One randomly chosen donor from the risk and protective diplotype groups was kept back for other studies, leaving 23 risk, 2 neutral, and 6 protective diplotype donors. Of these, all of the neutral and protective diplotype donors were analyzed. The 23 risk diplotype donors were subdivided into smokers at time of death and nonsmokers/ex-smokers; four of the smokers and five of the nonsmokers/ex-smokers were chosen at random from these two groups for analysis. 

Immunohistochemistry, microscopy, and image analysis were performed under blinded conditions, that is, without knowledge of the age, genotype, or clinical history of the donor. Six-millimeter-diameter trephine-generated punches of the macula (RPE–choroid and retina), centered on the fovea, were obtained. The discs of macular tissue were embedded in 10% agarose (wt/vol, type XI, low-gelling temperature; Sigma-Aldrich Corp., St. Louis, MO, USA) at 45°C, and tissue sections of 100-μm thickness were made by using a Vibratome 1000 (Vibratome, St. Louis, MO, USA). After extensive washing with PBS, the tissue sections were blocked by incubation at room temperature for 6 hours with PBS containing 1 mg/mL BSA, 1% (vol/vol) goat serum, and 0.1% (vol/vol) Triton X-100. Immunohistochemistry was performed by using 14 antibodies against markers of oxidative stress, inflammation, complement regulation and activation, and other molecules of interest (Table 3). For each experiment, the relevant primary antibody was diluted in blocking buffer, applied to tissue sections (200 μL/section), and incubated for 16 hours at 4°C. After washing with PBT (PBS containing 1 mg/mL BSA and 0.1% [vol/vol] Triton X-100; three separate washes of 15 minutes duration each, at room temperature), tissue sections were incubated with fluorescently labeled secondary antibody (either AlexaFluor-488 goat anti-mouse IgG or AlexaFluor-488 goat anti-rabbit IgG, or AlexaFluor-488 goat anti-mouse IgM/IgG for 10E4; all from Invitrogen, Waltham, MA, USA), diluted 1:200 in PBT, for 16 hours at 4°C. After washing with PBT (three separate washes of 15 minutes' duration each, at room temperature), tissue sections were mounted on Superfrost microscope slides (Electron Microscopy Sciences, Hatfield, PA, USA) with Fluoro-Gel mounting medium (containing 4′,6-diamidino-2-phenylindole [DAPI] as a nuclear counterstain; Electron Microscopy Services). Microscope slides were stored at 4°C in the dark for 1 week before immunofluorescence imaging. 

For experiments using the 3G10 antibody against heparan sulfate, tissue sections underwent enzymatic digestion with heparinase III from Flavobacterium heparinum (Amsbio, Cambridge, MA, USA), comprising 0.002 IU enzyme in 200 μL digestion buffer (0.1 M sodium acetate, 5 mM calcium chloride, pH 7.0) per tissue section, for 4 hours at 37°C, before blocking and antibody incubation steps. Control experiments were conducted where tissue sections were incubated with blocking buffer instead of primary antibody. Control experiments for procedures using the 3G10 antibody were conducted by incubation with digestion buffer without heparinase III, before staining. In all experiments, at least two tissue sections from the macular punch for each donor were stained for each antibody. 

Images were obtained by using a Fluoview 1000 laser scanning confocal microscope (Olympus America, Melville, NY, USA), using standardized methodology. In all cases, identical settings were used for image acquisition; the HV (sensitivity) setting had previously been optimized for each primary antibody and was maintained constant between all donors for each probe to ensure consistency. The confocal microscopy specifications were as follows: magnification ×20; AlexaFluor-488 laser intensity 6% (HV 350–400, predetermined for each antibody); DAPI laser intensity 4% (HV 400); 80-μm aperture; 20 μs/pixel; Kalman averaging (×2). For each tissue section examined, three images were obtained at random locations (approximately 1-mm diameter each), with the locations chosen under DAPI viewing conditions (as opposed to those for AlexaFluor-488). Since either two or three tissue sections were stained for each antibody for each donor, with three images obtained for each tissue section, a total of six or nine images were analyzed in each case. 

Gray scale images of macular RPE–choroid and retina were analyzed by using ImageJ64 (v1.40g; http://imagej.nih.gov/ij/; provided in the public domain by the National Institutes of Health, Bethesda, MD, USA). For all antibodies (except where stated otherwise), staining was quantified in four anatomic areas of interest, specifically, the retinal pigment epithelium (RPE), Bruch's membrane (BM), choriocapillaris (CC), and choroidal stroma (CS). For the antibodies against TCC, C3/C3b, and vitronectin, staining was also quantified in the choriocapillaris intercapillary septa (CC IS), as these structures are labeled very clearly and intensely by these antibodies (see Figs. 1B, 1D, 1F, 2F). Finally, for antibodies against carboxymethyl-lysine (CML), 4-hydroxynonenal (HNE), membrane cofactor protein (MCP), and decay accelerating factor (DAF), staining was also quantified in the retina, as these markers of oxidative stress and cell-surface homologues of CFH are known from previous studies^29–31 to be present in the human neurosensory retina. 

For each image, a polygon was drawn around the relevant anatomic structure, across the whole length of the tissue imaged (see Supplementary Fig. S1 for demonstration of segmentation into relevant anatomic areas), and ImageJ was used to calculate the mean fluorescence per unit area within the polygon. This process was repeated for all images, generating six or nine values of fluorescence for each anatomic area with each antibody for each donor, and the mean of these values was obtained. Similar analysis was performed on the images of the control/blank tissue sections. For each antibody on each donor, the mean blank signal was then subtracted from the mean test signal to generate the final representative value. 

Primary statistical analysis was conducted by using the Mann-Whitney U test. Where primary statistical analysis identified a significant difference by genotype and/or smoking status, secondary statistical analysis by two-way analysis of variance (ANOVA) was also applied following logarithmic transformation of data to stabilize variance.³² 

Immunohistochemistry for complement activation products in human macular RPE–choroid tissue was performed and quantified for all donors, under masked conditions. Donors that were homozygous risk at the CFH-to-F13B locus exhibited significantly higher levels of the TCC in macular BM (P = 0.03), CC (P = 0.04), and CC IS (P = 0.03) than homozygous protected donors (Figs. 1A, 1B; see Supplementary Fig. S2A for accompanying negative control experiments). In the CS, staining levels were weak (particularly with increased distance from the CC) and nonsignificantly higher in risk donors (P = 0.26); negligible staining was observed in the RPE. The differences observed between risk and protected donors were noted despite the fact that the risk donor group was younger on average than the protected group (mean, 66 vs. 72 years), where levels of TCC in human BM/choroid are known to increase with age,^17,18 and contained fewer donors with genetic risk at C3 (rs2231099; 2/9 vs. 4/6). The results were consistent for staining obtained with both Dako (Carpinteria, CA, USA) and Quidel (San Diego, CA, USA) antibodies against the TCC (Table 3), with similar staining patterns observed for both antibodies. 

Moreover, the degree of staining for TCC was higher in those donors with positive smoking histories than in those without (Figs. 1C, 1D; and Supplementary Fig. S2B for negative controls). The level was significantly higher in BM (P = 0.05), CC IS (P = 0.03), and CS (P = 0.01) but did not meet statistical significance in CC (P = 0.14) by two-way ANOVA (undertaken as primary statistical analysis had already identified a significant difference by genotype). Again, this was despite the fact that the smoking group was younger on average than the nonsmoking group (mean, 66 vs. 72 years) and contained a similar proportion of donors with risk at C3 (4/10 vs. 2/7). 

Immunohistochemistry was also performed for the complement component and amplification product C3/C3b (using a monoclonal antibody that recognizes C3, C3b, iC3b, and C3dg). Donors homozygous risk at the CFH-to-F13B locus had higher levels of C3/C3b in macular BM (P = 0.08), CC (P = 0.02), and CC IS (P = 0.007), compared to homozygous protected donors (Figs. 1E, 1F; and Supplementary Fig. S2C for negative controls). No significant differences were observed according to smoking status in the BM (P = 0.33), CC (P = 0.83), or CC IS (P = 0.81) by two-way ANOVA. Staining levels were extremely weak in the CS (i.e., labeling was confined for the most part to the CC, as observed previously¹⁶), and negligible in the RPE. 

Complement factor I (CFI) is an important regulator of the complement system; in the alternative pathway, it cleaves and inactivates C3b (using CFH as a cofactor) to prevent excessive complement activation on host surfaces.³³ Complement factor I labeling was weakly present throughout the RPE, BM, CC, and CS, as observed in previous studies.¹⁶ However, no significant differences were observed in the levels of CFI staining according to genotype or smoking, respectively, in the RPE (P = 0.86, P = 0.31), BM (P = 0.16, P = 0.77), CC (P = 0.07, P = 0.22), or CS (P = 0.60, P = 0.53). In addition, CFP (properdin) is the only known positive regulator of complement activation and can initiate complement activation through stabilization of the alternative pathway convertases.³⁴ Again, weak labeling of CFP was present throughout the RPE, BM, CC, and CS, but no significant differences were observed in levels of its staining according to genotype or smoking, respectively, in the RPE (P = 0.41, P = 0.38), BM (P = 0.60, P = 0.38), CC (P = 0.77, P = 0.96), or CS (P = 0.73, P = 0.62). 

Membrane cofactor protein and DAF are cell-surface homologues of CFH and are able to regulate complement activation (in non–extracellular matrix environments).³⁵ Membrane cofactor protein labeling was present in the retina, RPE (abundant on its basal surface), CC, and CS, while DAF labeling was found in the retina, CC, and CS, but was very weak in the RPE, all as observed previously^16,31; there was no significant staining of BM for either protein (as expected for this extracellular matrix). No significant differences were observed according to genotype in staining levels in macular retina or RPE–choroid for MCP (retina: P = 0.73, RPE: P = 0.26, CC: P = 1.00, CS: P = 0.86) or DAF (retina: P = 0.52, RPE: P = 0.86, CC: P = 0.86, CS: P = 0.52). Similarly, no differences were observed according to smoking status. 

Labeling of the acute phase reactant CRP in macular tissue was generally moderate in the RPE and BM, and strong but variable between donors in the CC and CS (Fig. 2B), consistent with previous studies.^36,37 Indeed, donors with positive history of cigarette smoking had significantly higher levels of staining than those who had never smoked, in BM (P = 0.05) and CC (P = 0.04), but this did not meet statistical significance in the RPE (P = 0.19) or CS (P = 0.06) (Figs. 2A, 2B; and Supplementary Fig. S3A for negative controls). The difference was even more striking considering donors that continued smoking until death versus others: RPE (P = 0.04), BM (P = 0.01), CC (P = 0.05), and CS (P = 0.05). 

Interestingly, no difference was observed in CRP levels, based on genotype in the RPE (P = 0.86), BM (P = 0.95), CC (P = 0.73), or CS (P = 0.41). However, qualitative analysis did strongly suggest that cigarette smoking was associated with very substantial elevation in CRP levels in the homozygous risk donors but not the protected donors (Figs. 2A, 2B). Indeed, two-way ANOVA (undertaken as primary statistical analysis had already demonstrated a significant difference by smoking status) provided support for this idea; in CC, significance values for a positive effect were P = 0.02 (smoking), P = 0.59 (genetic risk), and P = 0.025 (interaction between smoking and genetic risk). 

The two biomarkers of oxidative stress used in this study were CML and HNE. Carboxymethyl-lysine is an advanced glycation end-product that is formed in tissues by nonenzymatic glycation and oxidation, and causes protein damage by cross-linking, changing tertiary structure, and altered enzymatic activity,³⁸ while HNE is a toxic product of lipid peroxidation that has been well characterized as a reliable marker of oxidative stress in tissues.³⁹ Labeling for both CML and HNE was observed consistently throughout the retina, RPE, BM, and choroid (Fig. 2D). However, donors with positive smoking history had higher levels of CML in the RPE (P = 0.04) and CS (P = 0.007; not quantified separately for CC) than those without, while no significant difference was observed in the BM (P = 0.26) (Figs. 2C, 2D; and Supplementary Fig. S3B for negative controls). For CML, no significant difference was observed according to genotype in the RPE (P = 0.86), BM (P = 0.44), or CS (P = 0.47). Staining levels for HNE were on average higher in donors with smoking history, but this tendency was not statistically significant in the RPE (P = 0.31), BM (P = 0.38), or CS (P = 0.56). As above, no difference was observed according to genotype in the RPE (P = 0.77), BM (P = 0.29), or CS (P = 0.71). 

Vitronectin is a common component of the extracellular matrix and is abundantly present in drusen⁴⁰; it can protect against complement-mediated damage, particularly through interactions with the TCC.⁴¹ Labeling for vitronectin was particularly concentrated around the CC, including CC IS, and BM (see Fig. 2F), but was relatively weak in both the RPE and CS. No significant difference in levels of staining for vitronectin was observed according to CFH-to-F13B genotype or smoking, respectively, in macular RPE (P = 0.95, P = 0.13), BM (P = 0.86, P = 0.53), CC (P = 0.48, P = 0.62), CC IS (P = 0.95, P = 0.70), or CS (P = 0.56, P = 0.38) (Figs. 2E, 2F; and Supplementary Fig. S3C for negative controls). 

Heparan sulfate is the major binding partner for CFH in human macular BM,^42,43 and the quantity of heparan sulfate in macular BM has been observed to decrease with age.⁴⁴ Heparan sulfate labeling (with either the 10E4 or 3G10 antibody) was present consistently throughout the retina, RPE, BM, CC, and CS layers, as we have observed in previous studies.^44,45 The level of staining with the 10E4 monoclonal antibody (which recognizes a common N-sulfated epitope in heparin sulfate⁴⁶) did not differ according to genotype or smoking, respectively, in RPE (P = 0.32, P = 0.19), BM (P = 0.64, P = 0.95), CC (P = 0.95, P = 0.95), or CS (P = 0.90, P = 0.95). By contrast, the level of heparan sulfate staining with the 3G10 monoclonal antibody (which recognizes heparan sulfate stubs after digestion with heparinase III) did not differ by genotype in the RPE (P = 0.60) or BM (0.38), but was higher in risk donors in the CC (P = 0.05) and CS (P = 0.02); the level was also higher in current smokers than others in the RPE (P = 0.03), BM (P = 0.03), and CC (P = 0.05), but not the CS (P = 0.59). 

Heparanase-1 is an important extracellular matrix enzyme that cleaves heparan sulfate chains in tissues and has been implicated in human disease including cancer, inflammation, and atherosclerosis.⁴⁷ Heparanase-1 labeling was found throughout the RPE, BM, and choroid, as we have observed previously.⁴⁴ However, no differences in levels of heparanase-1 staining were observed according to genotype in the RPE (P = 0.48), BM (P = 0.64), or CS (P = 1.0). While levels of staining were on average higher in donors with positive smoking history, these differences were not statistically significant in the RPE (0.07), BM (P = 0.09), or CS (P = 0.10). 

In this analysis, immunohistochemical results in macular RPE–choroid were examined for potential correlations between different molecules of interest. The level of staining for CRP and the TCC showed strong–moderate correlation in BM (r = 0.57), CC (r = 0.68), and CS (r = 0.85) (Fig. 3A). In addition, markers of oxidative stress were analyzed against levels of CRP staining in CS and showed moderate correlation (r = 0.61 for HNE and r = 0.51 for CML; Fig. 3B). Finally, markers of oxidative stress were analyzed against levels of TCC staining in CS and showed moderate correlation (r = 0.47 for HNE and r = 0.54 for CML; Fig. 3C). 

In this study, we used human macular tissue from donors with pure CFH-to-F13B diplotypes in conjunction with a panel of antibodies to investigate potential molecular determinants of chromosome 1–directed AMD, specifically, markers of oxidative stress, complement activation, and inflammation. Importantly, all donors were homozygous nonrisk at the ARMS2/HTRA1 locus on chromosome 10, in order that chromosome 1–directed pathways be assessed. Genetic risk at the CFH-to-F13B locus was associated with higher levels of complement activation at the RPE–choroid interface. Levels of complement activation were also higher in donors with history of cigarette smoking. In addition, cigarette smoking was associated with substantial elevations in levels of CRP in the macula, particularly in homozygous risk donors. Evidence was observed for increased levels of oxidative stress in the RPE–choroid of donors with positive smoking history. Finally, the observation of lower levels of C3/C3b in CFH-to-F13B protected donors supports the concept that donors with protective genotypes (specifically the I62V polymorphism and the CFHR3/1 deletion) may be relatively protected against the development of AMD specifically through enhanced CFH-mediated complement regulation. 

The strengths of this study includes the use of human donor macular tissue from a very large well-characterized eye repository that includes extensive genetic and clinical information on donor tissue. This enabled us to select donors with pure CFH-to-F13B diplotypes and without risk variants at the ARMS2/HTRA1 locus. This approach is critical for identifying the molecular determinants of chromosome 1–directed AMD, as distinct from disease driven by chromosome 10. In addition, it enabled us to select donors from similar age groups; ages of 55 to 79 years were chosen for this study in order to identify altered levels of relevant proteins in the predominantly preclinical phase of disease, that is, before macular destruction through the extensive inflammation, atrophy, and/or choroidal neovascularization and scarring processes that may accompany advanced AMD. Indeed, no donors used in this study had AMD diagnosed clinically before death or on fundal photography of postmortem tissue. Further strengths of the study included the ability to select donors with verified positive and negative histories of cigarette smoking in both genetic groups. 

Macular tissue from donors with pure diplotypes and uniformly short postmortem times was used in conjunction with a panel of well-characterized antibodies, much larger than numbers used in many previous studies, and including diverse markers involved in oxidative stress, complement activation, regulation, and inflammation (processes considered central to chromosome 1–directed AMD pathogenesis^14,16). Most of these antibodies have been used and validated in previous immunohistochemical studies of ocular tissue,^{16,17,36,44,45,48–50} and more than one antibody was used in some cases (e.g., for the TCC and for heparan sulfate). The entire study, from immunohistochemistry to microscopy and image analysis, was performed blinded to donor genotype and clinical status, and under standardized conditions, ensuring maximum confidence in any observed differences between groups. This clearly revealed that CFH-to-F13B genotype, together with smoking status, are major variables in determining levels of complement activation at the human macular RPE–choroid interface. Hence, a clear link was demonstrated between known epidemiologic risk factors for AMD and molecular pathology at the anatomic site of AMD formation. 

The main limitation of the study was relatively modest sample size. When the genotype of 1601 donors was analyzed, donors with pure CFH-to-F13B diplotypes and without risk variants at the ARMS2/HTRA1 locus were found to be rare, so the sample size was small. For similar reasons, it was not possible to age-match the groups closely, though we did find increased complement activation in homozygous risk donors despite this group being younger on average than the protected group. We also acknowledge that immunofluorescence is semiquantitative, that is, fluorescence intensity is not always proportional to the amount of antigen, though all staining and imaging protocols were performed in a standardized manner with identical settings. For this reason, and because of the relatively small sample size, primary statistical analysis was performed by using nonparametric testing (by Mann-Whitney U test). Where primary statistical analysis identified a significant difference by genotype and/or smoking status, secondary statistical analysis was undertaken by using parametric testing (by two-way ANOVA). Uncertainty over the normal distribution of these data means that the ANOVA results should be interpreted cautiously, though data were log-transformed to stabilize variance before testing.³² 

Several previous studies^17–19,51 have reported the presence of TCC in the Bruch's membrane/choriocapillaris complex, based on immunolocalization studies. However, there is no good evidence that any known antibodies can distinguish between the different forms of the TCC.⁵² Terminal complement complex (C5b-9) can occur as a soluble form (SC5b-9), which binds vitronectin and is nonlytic, or as a membrane-bound form, which can recruit more C9 to form the lytic membrane attack complex (MAC). Therefore, the presence of extracellular TCC in Bruch's membrane and extracellular components of the choriocapillaris could indicate local production of SC5b-9 and therefore, local complement activation, MAC that has blebbed off cell membranes, or deposition of blood-borne SC5b-9. The reported relative concentration in the macular region does however favor the case for local formation of TCC.^51,53 

One previous study has reported increased levels of the TCC in the RPE–choroid of donors homozygous risk at the Y402H polymorphism in CFH by ELISA (P = 0.04; n = 8 for high risk and n = 10 for low risk),¹⁹ in juxtamacular tissue, though other important donor variables are not reported in the article, including age, genetic risk at C3 and ARMS2/HTRA1, and smoking status. A recent article by the same group¹⁸ reports that levels of the TCC increase significantly with age, with AMD, and with risk at CFH_Y402H, but the study does not analyze TCC levels by CFH-to-F13B genotype in the absence of risk at the ARMS2/HTRA1 locus. This is important, as AMD may comprise at least two partially distinct disease entities, one driven predominantly by risk at chromosome 1 and the other by risk at chromosome 10. For a refined understanding of potentially separate biological pathways involved, it is therefore essential to distinguish between AMD caused by variants at either locus. Indeed, this is the first study (to our knowledge) that performed immunolocalization of complement activation products and inflammatory markers in human macular tissue on a set of donors with pure CFH-to-F13B diplotypes, no risk at ARMS2/HTRA1, together with detailed smoking history. Despite the modest sample size presented here, this approach may be extremely fruitful in elucidating the precise pathobiology underpinning AMD driven by CFH-to-F13B genotype versus ARMS2/HTRA1. 

Two previous studies have examined the level of CRP in human macular tissue, one according to CFH_Y402H genotype³⁶ and one according to AMD status.³⁷ Johnson et al.³⁶ have reported that CFH homozygote risk donors have significantly higher levels of CRP in the choroid by immunohistochemistry than homozygote nonrisk donors (n = 6 and n = 9, respectively). However, the smoking status of these donors is not reported; given the small sample size of the risk donors (n = 6), it is possible that CRP levels may have been elevated in donors through a combination of positive smoking history and CFH risk, rather than through the CFH risk alone. Bhutto et al.³⁷ have performed macular immunohistochemistry for CRP on 18 donors with AMD and 10 aged controls, and they have observed that staining intensity is significantly higher in AMD donors. Only three of the 18 donors were labeled as having positive smoking history; this proportion seems low for this age group, suggesting that accurate smoking history may not have been available. Indeed, many donors in the AMD group were labeled as having chronic obstructive pulmonary disease (COPD; usually caused by cigarette smoking; 4/8 in the early AMD group and 3/6 in the geographic atrophy group), which raises the possibility that smoking status (alone or in combination with CFH genetic risk) rather than AMD is the primary associate of raised CRP levels. 

Other molecules were examined in this study owing to existing interest in their potential involvement in AMD pathogenesis, including markers of oxidative stress, heparan sulfate, and complement regulators such as CFI and vitronectin. Evidence for elevated levels of macular oxidative stress with cigarette smoking was observed, together with some correlation between levels of oxidative stress and complement activation; this supports the idea that oxidative stress is strongly implicated in AMD pathogenesis.^26,54 Heparan sulfate is the main binding partner for CFH in human macular BM^42,43; its levels in this extracellular matrix have recently been shown to decrease with age, potentially leading to reduced quantities of CFH available to prevent complement activation.⁴⁴ Genotype was not found to alter levels of heparan sulfate in BM (though 3G10 labeling was higher in CC and CS with the risk diplotype). However, the level of 3G10 but not 10E4 staining in the RPE–choroid was higher in smokers. 3G10 recognizes heparan sulfate stubs after bacterial heparinase III digestion, so this result suggests that there are more heparan sulfate chains in smokers, while the overall amount of heparan sulfate (as assessed using the 10E4 antibody) was not different between smokers and nonsmokers. A possible explanation is that smoking results in heparan sulfate chain degradation, and to compensate there is increased heparan sulfate proteoglycan synthesis. 

Overall, these findings enhance our understanding of AMD pathogenesis, specifically the pathobiology of chromosome 1–directed AMD. The findings that CFH-to-F13B risk and cigarette smoking are both associated with increased complement activation in macular RPE–choroid supports the hypothesis that local complement dysregulation is central to this form of AMD. It also suggests that therapeutic strategies to inhibit complement activation locally in the eye may be effective for individuals with chromosome 1–driven disease, though patients with mixed disease (i.e., driven by chromosome 10 also) may require different therapeutic strategies. Similarly, the close correlation between levels of complement activation and the inflammatory marker CRP reinforces the idea that complement dysregulation and chronic local inflammation are intimately related at the macular RPE–choroid interface in early AMD. 

In conclusion, genetic risk at the CFH-to-F13B locus (in the absence of risk at the ARMS2/HTRA1 locus) was associated with higher levels of complement activation at the human macular RPE–choroid interface, as was history of cigarette smoking. Levels of inflammation were substantially elevated in CFH-to-F13B risk donors with history of cigarette smoking, which was also associated with increased oxidative stress in all donors. Examination of human macular tissue from donors with “pure” diplotypes allows assessment of AMD-associated pathways that are driven solely by the CFH-to-F13B gene locus. These findings have important implications related to the identification of chromosome 1–directed pathways and therapeutic targets. 

We gratefully acknowledge the assistance of Anthony Day, PhD (Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester), with pilot studies related to this work. We also acknowledge the valuable contributions of Debra Schaumberg, MPH (Center for Translational Medicine, John A. Moran Eye Center, Department of Ophthalmology and Visual Sciences, University of Utah), and Andrew Dowsey, DPhil (Centre for Advanced Discovery and Experimental Therapeutics [CADET], University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester), for advice with statistical analysis. 

Supported by the Fulbright/Fight for Sight UK-US Scholarship 2013/14 (TDLK). 

Disclosure: T.D.L. Keenan, None; M. Toso, None; C. Pappas, None; L. Nichols, None; P.N. Bishop, None; G.S. Hageman, Allergan, Inc. (F), Ophtherion, Inc. (I), Voyant Biotherapeutics (I), AGTC (C), Gerson Lehrman (C), Novartis Pharmaceuticals (C), Sequenom, Inc. (C), P