HTRA1-AS1 , an ARMS2 -region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients

HTRA1-AS1, an ARMS2-region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search HTRA1-AS1 , an ARMS2 -region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients Ping-Wu Zhang , Zi-He Wan , Sheng Liu , Jie Wang , Srinivasa Sripathi , Weifeng Li , Junyeop Ahn , Sean Li , Laura Fan , Cynthia A. Berlinicke , Jiang Qian , Shannath L. Merbs , Donald J. Zack doi: https://doi.org/10.1101/2025.10.29.25338834 Ping-Wu Zhang 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: pzhang5{at}jhmi.edu smm8vp{at}uvahealth.org donzack{at}gmail.com Zi-He Wan 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sheng Liu 2 Department of Medical and Molecular Genetics, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine , Indianapolis, IN, 46202, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jie Wang 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Srinivasa Sripathi 3 Henderson Ocular Stem Cell Laboratory, Retina Foundation of the Southwest , Dallas, 75231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Weifeng Li 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Junyeop Ahn 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sean Li 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laura Fan 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cynthia A. Berlinicke 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jiang Qian 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shannath L. Merbs 4 Department of Ophthalmology, University of Virginia School of Medicine , Charlottesville, VA, 22908, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: pzhang5{at}jhmi.edu smm8vp{at}uvahealth.org donzack{at}gmail.com Donald J. Zack 1 Department of Ophthalmology, Stem Cell Ocular Regenerative Medicine Center, Wilmer Eye Institute, Johns Hopkins University School of Medicine ; Baltimore, MD, 21231, USA 5 Solomon H. Snyder Department of Neuroscience, Department of Molecular Biology and Genetics, Department of Genetic Medicine, Center for Nanomedicine at the Wilmer Eye Institute, The Johns Hopkins University School of Medicine , Baltimore, Maryland, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: pzhang5{at}jhmi.edu smm8vp{at}uvahealth.org donzack{at}gmail.com Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Purpose The human 10q26 locus is a major genetic risk factor for age-related macular degeneration (AMD). Fine mapping by linkage and large-scale genome-wide association studies (GWAS) has narrowed this region to a 30-kb interval encompassing the ARMS2 and HTRA1 genes. However, the causative gene(s), risk variants, and underlying pathogenic mechanisms remain unresolved. Methods Long non-coding RNA (lncRNA) candidates within the ARMS2–HTRA1 region were identified using human postmortem retinal RNA-seq data and public databases (NCBI, Ensembl). Candidate transcripts were validated by RT-PCR and Sanger sequencing. Published single-cell RNA-seq datasets were analysed to define cell type–specific expression, and RNA levels were compared between AMD and non-AMD donor retinas. Additionally, expression changes were assessed in human iPSC-derived retinal pigment epithelium (RPE) cells exposed to cigarette smoke extract (CSE) and paraquat (PQT). Results We identified and validated a lncRNA, HTRA1-AS1 , and its transcript variants ( ENST00000647969.1 ) within the ARMS2 locus. HTRA1-AS1 overlaps ARMS2 and is transcribed in the antisense orientation. It is predominantly expressed in rod photoreceptors, Müller glia and Choroid/RPE, and its retinal expression was significantly reduced in AMD compared with controls (43 AMD donors vs. 44 controls, p = 0.007). By contrast, HTRA1 mRNA showed no significant difference (p = 0.121). Furthermore, ENST00000647969.1, HTRA1-AS1 and ARMS2 expression increased dramatically, up to 101-fold, 8-fold and 75-fold, respectively, in induced pluripotent stem cells (iPSC)-derived RPE cells following cigarette smoke extract (CSE)-induced oxidative stress but showed no significant change after paraquat treatment. Conclusion These findings suggest that HTRA1-AS1 , a dysregulated lncRNA within the ARMS2 locus, may act as a non-coding element contributing to transcriptional mis-regulation underlying AMD pathogenesis. Introduction Age-related macular degeneration (AMD), the leading cause of irreversible blindness in the elderly, is characterized by the progressive degeneration of photoreceptors and retinal pigment epithelial (RPE) cells. 1 In 2019, the prevalence of early-stage AMD among adults aged 40 years and older in the United States was estimated at 11.64%. 2 While aging, smoking, and diet constitute key environmental factors, numerous studies have established the importance of genetic contributions to AMD risk. 3 Although approximately 70–80% of AMD cases are sporadic, genetic factors have been suggested to account for up to 70% of overall disease risk. 4 – 6 This contribution is comparable to that observed in Alzheimer’s disease (AD) and significantly greater than in other common neurodegenerative disorders like amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). For comparison, 90–95% of ALS and PD cases are sporadic, and known pathogenic variants explain only 10–20% of ALS and ∼14% of PD susceptibility. 7 – 10 Conversely, in late-onset AD, APOE ϵ4 is the strongest risk factor, and genome-wide association study (GWAS) identified variants collectively explain ∼70% of disease susceptibility. 11 , 12 AMD risk factors are complex and multigenetic. To date, more than 40 genes and loci have been associated with AMD, with the complement factor H ( CFH ) locus on chromosome 1q31 and the ARMS2/HTRA1 locus on chromosome 10q26 showing the strongest associations. 6 , 13 Together, these two loci account for more than 50% of the inherited risk for AMD. 14 The remaining genetic risk is distributed across a variety of more minor loci that together account for about 20% of heritability. 4 , 6 Ethnic variability has been observed for CFH variants, which show strong associations in Caucasian populations but inconsistent replication in some east Asian cohorts. 15 – 17 In contrast, the ARMS2/HTRA1 locus has demonstrated robust associations across diverse populations, with no clear inter-ethnic differences. Furthermore, rod-mediated dark adaptation (RMDA) - a functional biomarker of early AMD - has been consistently linked to ARMS2 , but not CFH risk alleles, even in individuals without overt disease. 18 At the functional level, the causal variation at the CFH locus is relatively well defined, implicating its role as a central regulator of the complement pathway. By contrast, the precise biological contribution of the ARMS2/HTRA1 locus to AMD remains incompletely understood. HTRA1 encodes a serine protease, but the function of ARMS2 is still unclear, and the specific gene(s), risk variants, and molecular mechanisms driving AMD susceptibility at 10q26 are not yet established. 5 , 19 Given that the ARMS2/HTRA1 locus remains one of the most strongly associated yet mechanistically least understood regions in AMD genetics, we sought to perform an in-depth investigation of this genetic interval. Our study aimed to identify novel coding or noncoding transcripts within the ARMS2/HTRA1 region that may contribute to AMD pathogenesis and provide mechanistic insight into how this locus confers risk. Ethics statement All aspects of this study were conducted in accordance with the principles of the Declaration of Helsinki, with informed consent being obtained from all participants. This project was approved by the Johns Hopkins University School of Medicine Institutional Review Board (IRB). Material and Methods Human AMD eye samples Post-mortem eye tissues (AMD and non-AMD controls) were obtained from the National Disease Research Interchange (NDRI, Philadelphia, USA) and transported on wet ice. Processing of all samples occurred within 48 hours of death. Before retina isolation, macular photography was performed to document pathology. AMD samples were included only if they had documented clinical history and gross macular pathology consistent with disease. All tissue handling and processing procedures complied with the ARVO Best Practices for Using Human Eye Tissue in Research (Nov 2021). RNA Extraction from human retinal tissues Total RNA was extracted from ∼50 mg of retinal tissue using TRIzol (Thermo Fisher Scientific, Invitrogen, USA) and purified with the PureLink RNA Mini Kit (Thermo Fisher Scientific, Invitrogen, USA), including on-column DNase digestion (Thermo Fisher Scientific, Invitrogen, USA). Following homogenization in 600 µL TRIzol, samples underwent chloroform extraction and ethanol precipitation. RNA was purified using spin cartridges (Thermo Fisher Scientific, Invitrogen, USA) and eluted in RNase-free water. RNA concentration and purity were measured on a NanoDrop spectrophotometer (Thermo Fisher Scientific, USA), and samples with A260/280 ratios between 1.7 and 2.1 were used for downstream experiments. Human iPSC Culture and RPE Differentiation Human-induced pluripotent stem cells hiPSCs; EP1 line were cultured and differentiated into RPE monolayers following established protocols. 20 Briefly, hiPSCs were maintained on growth factor– reduced Matrigel (BD Biosciences) in mTeSR1 medium (Stem Cell Technologies) under 10% CO 2 and 5% O 2 , with expansion promoted by 5 μM blebbistatin (MilliporeSigma). For differentiation, cells were seeded at 35,000 cells/cm 2 in mTeSR1 until confluency, then switched to differentiation medium (DMEM/F12 supplemented with 15% knockout serum, 2 mM glutamine, 1% nonessential amino acids, 0.1 mM mercaptoethanol, 1% antibiotic–antimycotic, and 10 mM nicotinamide, all are from Thermo Fisher Scientific, USA) for ∼50 days. Differentiating RPE cells were dissociated with 0.25% collagenase IV (Thermo Fisher Scientific, USA) and AccuMAX (MilliporeSigma, USA) to generate a single-cell suspension, then re-plated on Matrigel-coated plates. Cells were matured for 2–3 months in RPE medium (70% DMEM, 30% Ham’s F12, 2% B-27 supplement, and 1% antibiotic–antimycotic, all were from Thermo Fisher Scientific, USA). Cigarette Smoke Extract (CSE) and paraquat treatments for iPSC-derived RPE monolayers Human iPSC-derived RPE monolayers were differentiated using our established methods and cultured for eight weeks to achieve mature RPE cultures. 21 The mature monolayers were then treated for 48 hours with Cigarette Smoke Extract (CSE) (Murty Pharmaceuticals, USA) and paraquat (MilliporeSigma, USA) at three lethal dose (LD) concentrations: LD25, LD50, and LD75 (doses for CSE: 125, 250, and 500 μg/mL, respectively; doses for PQT: 100, 300, and 600 μM, respectively). The CSE was prepared in DMSO, with the final solution containing 40mg/mL condensate. Following treatment, total RNA was extracted from the RPE monolayers using RNeasy Mini Kit (QIAGEN, USA). RNA purity and concentration were assessed using NanoDrop™ spectrophotometry (Thermo Fisher Scientific, USA), and only samples with A260/A280 ratios between 1.8 and 2.1 were used for downstream qPCR analysis. Reverse transcription and Quantitative PCR (qPCR) Total RNA was reverse-transcribed into cDNA using either the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, USA) or the iScript™ cDNA Synthesis Kit (Bio-Rad, USA). Quantitative PCR (qPCR) was then performed on a CFX-384 Real-Time PCR system using iTaq Universal SYBR Green Supermix (Bio-Rad, USA). All reactions were conducted in biological triplicates. Relative gene expressions were calculated using the geometric mean of two housekeeping genes, GAPDH and 18S (use a 100-fold dilution of 18S cDNA for qPCR analysis), for normalization. Primer sequences are detailed in Supplementary Table S1. RNA-sequencing (RNA-seq) and data analysis Published RNA-seq datasets were re-analysed for expression of genes within the PLEKHA1– ARMS2–HTRA1 locus. 22 Reads were mapped to the region of interest and quantified using standard pipelines. Sanger Sequencing DNA sequencing was performed at the Johns Hopkins Genetics Resources Core Facility using the Applied Biosystems 3730xl DNA Analyzer (Thermo Fisher Scientific, USA). Software and Statistical Analysis Data were analysed using GraphPad Prism (GraphPad Software10.3, USA) and Microsoft Excel. Statistical significance was assessed with unpaired two-tailed Student’s t-tests unless otherwise indicated. Data are presented as mean ± SEM (n = biological replicates). ns = not significant; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. A p-value < 0.05 was considered statistically significant. AlphaFold3 was used for predicting the three-dimensional structures of the putative peptide coding regions. Results RNA-seq identifies aligned-read peaks overlapping HTRA1-AS1 Reanalysis of RNA-seq datasets from macular retina, peripheral retina, and RPE/choroid tissues across the ARMS2–HTRA1 locus revealed two prominent read-alignment peaks upstream and one downstream of ARMS2 , consistently detected in both retinal and RPE/choroid samples ( Figure 1 ). HTRA1 exhibited robust expression across all ocular tissues (100–550 FPKM) with no marked preference between retina and RPE, whereas ARMS2 expression was minimal and largely confined to the retina. The antisense transcript HTRA1-AS1 (annotated on NCBI as predicted HTRA1 and ARMS2 antisense RNA 1), together with ENST00000647969 . 1 , were expressed at modest levels (∼30–50 FPKM), representing only a small fraction of HTRA1 expression. These antisense peaks correspond to low-abundance noncoding transcription within the 10q26 risk interval, supporting the presence of additional regulatory elements in this region. Download figure Open in new tab Figure 1. RNA-seq expression of 10q26 locus genes in human ocular tissues. Genomic organization of PLEKHA1, ARMS2 , and HTRA1 is shown, with exons represented by thick boxes and introns by lines. The antisense transcript HTRA1-AS1 and ENST00000647969 . 1 are also shown in orange, overlapping the ARMS2 and HTRA1 loci. Additional RNA aligned-reads peaks were detected in the ARMS2 region and overlap with lncRNA HTRA1-AS1 gene and another transcript variant ENST00000647969 . 1 . Validation of lncRNA HTRA1-AS1 and transcript variants Database searches identified multiple long non-coding RNAs (lncRNAs) overlapping ARMS2 . Ensembl listed four candidates ( ENST00000650300 . 1, ENST00000647969 . 1, ENST00000811415 . 1 , and ENST00000811416 . 1 ), and NCBI annotated HTRA1-AS1 ( LOC105378525 ) with four predicted transcript variants (XR_946382–XR_946385). All were transcribed antisense to ARMS2 ( Figure 2A ). Download figure Open in new tab Figure 2. Schematic portraying the overlap of the association peak with the ARMS2 gene and lncRNA variants overlap with ARMS2 gene. (A) LncRNA candidates and their locations. Genomic map of the PLEKHA1 – ARMS2 – HTRA1 region on chromosome 10q26, illustrating annotated protein-coding genes (blue, yellow and coral), and several lncRNAs (shaded in green, orange, and grey). Coordinates are given in mega base (Mb). HTRA1-AS1 (grey) and predicted four transcript variants (X2–X5, shown in dark blue) are located antisense to the ARMS2 gene. Several other lncRNAs ( ENST00000647969 . 1, ENST00000650300 . 1, ENST00000681145 .1, and ENST00000681146 . 1 ) are positioned within or near the ARMS2 locus, suggesting potential regulatory roles. Exons are indicated by boxes and introns by connecting lines. Direction of transcription is shown by arrows. ( B) Boundary sequences of exons for lncRNA ENST00000647969 . 1 and HTRA1-AS1 . RT-PCR and Sanger sequencing confirmed expression and boundary sequences of HTRA1-AS1 and ENST00000647969 . 1 in human retinas ( Figure 2B ). HTRA1-AS1 contains three exons (457 bp, 1417 bp, and 2881 bp, total 4755 bp) with sequence segments provided. ENST00000647969 . 1 includes two exons (182 bp, 385 bp, total 566 bp). Other predicted variants were weakly or not detected. ENST00000647969 . 1 appears to represent an alternative splice isoform of HTRA1-AS1 . HTRA1-AS1 is downregulated in human AMD retinas To assess the relationship between lncRNA HTRA1-AS1 expression and age-related macular degeneration (AMD), we collected human AMD and non-AMD control donor eyes from the National Disease Research Interchange (NDRI) over a period of more than five years. Donor demographic and clinical characteristics are summarized in Table 1. Most donors were White, and the two groups were age- and sex-matched. The mean donor age was 81.4 years in the control group and 82.5 years in the AMD group. Sex distribution was also comparable (control: 19 males, 24 females; AMD: 22 males, 21 females). Representative images of control and AMD eyes are shown in Figure 3A . Download figure Open in new tab Figure 3. RT-qPCR analysis of RNA expression in control and AMD donor retinas. (A) Representative macular images from control and AMD eyes. (B) HTRA1-AS1 expression is reduced in AMD (p < 0.01). (C) Transcript ENST00000647969 . 1 is decreased in AMD (p 0.05). HTRA1-AS1 and ENST00000647969 . 1 were significantly downregulated in AMD eyes (p = 0.007 and p = 0.041, respectively; Figure 3B, 3C ). In contrast, HTRA1 mRNA levels did not differ significantly between AMD and controls (p = 0.121; Figure 3D ). ARMS2 expression was extremely low (Ct >34) in our samples and not reliably quantifiable. Cell-type expression profiles of HTRA1-AS1 and HTRA1 To characterize the cell-type and regional expression patterns of HTRA1-AS1, HTRA1 , and transcript ENST00000647969 . 1 , we analyzed publicly available single-cell RNA sequencing datasets from human retina and RPE/choroid tissues. HTRA1-AS1 exhibited cell-type specific expression, with prominent enrichment in photoreceptors, particularly rods and cones, as well as Müller glia and RPE/choroid ( Figure 4A, 4B ). Similarly, transcript ENST00000647969 . 1 showed a comparable expression pattern to HTRA1-AS1 , with enrichment in photoreceptors and Müller glia, but low regional expression in both macular and peripheral tissues ( Figures 4C and 4D ). In contrast, HTRA1 displayed a broader expression profile, with detectable levels across multiple retinal cell types including photoreceptors, astrocytes, and microglia ( Figure 4E ). Notably, HTRA1 was robustly expressed across all retinal and RPE/choroid regions, with comparable expression levels in both macula and peripheral tissues ( Figure 4F ). These data suggest that while HTRA1 is widely expressed across retinal compartments, HTRA1-AS1 and ENST00000647969 exhibit more cell-type restricted expression patterns with limited regional variation, pointing to potentially distinct regulatory roles in specific retinal cell populations. Download figure Open in new tab Figure 4. Single-cell expression profiles of lncRNAs and HTRA1 across ocular cell types and tissue regions. Violin plots show the expression distributions of HTRA1-AS1, ENST00000647969 . 1 , and HTRA1 across various ocular cell types and tissue compartments derived from human donor eyes. Expression levels are normalized and plotted per cell type or tissue region. (A) HTRA1-AS1 (C) ENST00000647969(E) HTRA1 . Color coding indicates cells from macula (M) and peripheral (P) regions. ( B, D, F ) Regional expression of the same genes across four tissue compartments Available data indicate that HTRA1-AS1 and ENST00000647969 . 1 are primarily expressed in rod photoreceptors, Müller glia and Choroid/RPE, whereas HTRA1 is enriched in horizontal cells and moderately expressed in rods, cones, astrocytes, Müller glia, and RPE/choroid. Minimal or no HTRA1 expression was detected in microglia, bipolar, ganglion, or Amacrine cells. HTRA1 mRNA expression was notably higher in RPE/choroid compared to retina in both peripheral and macular regions. However, HTRA1-AS1 and ENST00000647969 . 1 did not show significant cellular differences in expression between the retina and RPE/choroid ( Figure 4A–F ). Cigarette smoke extract (CSE), but not paraquat (PQT), selectively induces dose-dependent upregulation of HTRA1-AS1 and ARMS2 mRNA Because cigarette smoking is a major risk factor for AMD, we investigated the transcriptional response of HTRA1-AS1 and neighbouring genes to CSE in iPSC-derived RPE cells. CSE treatment elicited a robust, dose-dependent induction of ENST00000647969 . 1, HTRA1-AS1 , and ARMS2 transcripts, with the highest increases observed at the LD75 dose (101.4-fold, 8.0-fold, and 75.3-fold, respectively; Figure 5A, 5B, 5D ). HTRA1 mRNA expression also rose at higher CSE concentrations, though to a lesser extent, reaching a maximum 2.8-fold increase ( Figure 5C ). Download figure Open in new tab Figure 5. Quantitative RT-PCR analysis of the expression of ENST00000647969 . 1, HTRA1-AS1, HTRA1 , and ARMS2 mRNA in cells following treatment with increasing concentrations of CSE (Panels A–D) or PQT (Panels E– H). Treatment groups included untreated control (CTL), vehicle control (DMSO), and three lethal dose (LD) levels: LD25, LD50, and LD75. mRNA levels were normalized to GAPDH and 18S. (A–D). To test if this response was specific to CSE or a general reaction to oxidative stress, we treated cells with paraquat (PQT), a classic oxidative stress inducer. In contrast, PQT treatment across comparable sublethal concentrations (LD25–LD75) did not significantly alter the expression of any of the tested transcripts ( Figure 5E–H ). These findings demonstrate that CSE selectively drives the dose-dependent induction of HTRA1-AS1 and ARMS2 in RPE cells, suggesting a smoking-specific regulatory effect on this AMD-associated locus. Discussion A major challenge in AMD research is reconciling the strong genetic associations at the ARMS2/HTRA1 locus with the limited molecular evidence supporting a causative mechanism. Previous investigations have largely focused on the protein-coding genes ARMS2 and HTRA1 . 23 In the present study, we broadened this scope to noncoding transcripts within the 10q26 interval, which is consistently implicated by GWAS and transcriptomic data. Importantly, RNA read densities across this region often exceeded those mapped to ARMS2 exons, suggesting that additional regulatory elements beyond ARMS2 and HTRA1 may contribute to disease risk. The identification of disease-associated genes typically relies on three strategies: candidate gene analysis, linkage studies with whole-exome or whole-genome sequence data in familial disease, and GWAS with targeted follow-up in sporadic disease. By integrating retinal RNA-seq with NCBI and Ensembl annotations, we identified a novel antisense lncRNA, HTRA1-AS1 , (and its isoforms) that overlap with ARMS2 . Although several lncRNAs have been implicated in AMD, 24 , 25 none of the previously described lncRNAs are located within the ARMS2/HTRA1 risk locus. A recent preprint reported the same lncRNA ( BX842242 . 1/ENSG00000285955 ) associated with reticular pseudodrusen (RPD), with elevated expression correlating with reduced HTRA1 levels. 26 In contrast, our data demonstrate that HTRA1-AS1 is significantly downregulated in AMD retinas, whereas HTRA1 mRNA expression was unchanged between cases and controls. Such discrepancies likely reflect differences in tissue sources, retinal layers analyzed, or disease context, underscoring the complexity of regulatory networks within this locus. Since the original 2006 discovery report for ARMS2-HTRA1 region, 27 attempts to directly link ARMS2 or HTRA1 expression with AMD have yielded inconsistent results, often due to limited sample sizes. 19 By analyzing 43 AMD and 44 control retinas, our study represents the largest cohort to date demonstrating lncRNA dysregulation at this locus. Specifically, HTRA1-AS1 was reduced in AMD retinas but was robustly induced by cigarette smoke extract (CSE) in iPSC-derived RPE cells. Interestingly, this effect was not observed with paraquat, a general oxidative stressor, indicating that ARMS2 and HTRA1-AS1 are not simply stress-inducible transcripts. Instead, their selective upregulation by CSE points to the involvement of specific, non-oxidative molecular cues derived from cigarette smoke. The modest but significant increase in HTRA1 expression further supports a coordinated, gene-specific response. Together, these findings suggest that smoking may potentiate disease-associated transcriptional programs at the ARMS2– HTRA1 locus, providing a direct mechanistic link between environmental and genetic risk factors in AMD. The precise functional role of HTRA1-AS1 remains to be elucidated. Although antisense lncRNAs frequently regulate the transcription or stability of neighboring genes, 23 our data argue against a simple repressive interaction with ARMS2 . Increasing evidence also indicates that some lncRNAs can produce bioactive micropeptides. For instance, the LIL peptide, derived from a two-amino-acid open reading frame, promotes cell growth. 28 Notably, the AMD-associated SNP rs61871745 (G/A; A as the risk allele) is located within predicted coding regions of HTRA1-AS1 and ENST00000647969 . 1 . The risk allele A may induce a nucleotide substitution (C→T) that changes the predicted encoded codon from A C C to A T C (Thr→Ile) within one of the putative open reading frames. 29 Structural modeling suggests that this amino acid substitution could play a role in the predicted peptide ( Figure. 6 ). Whether HTRA1-AS1 exerts its effects solely as a regulatory lncRNA, encodes a functional micropeptide, or possesses dual roles remains an intriguing question for future investigation. Download figure Open in new tab Figure 6. Predicted coding sequences and protein structure for HTRA1-AS1 and ENST00000647969 . 1 . A and B , Nucleotide and corresponding amino acid sequences of the putative open reading frames (ORFs) identified in the 5′–3′ Frame 3 of HTRA1-AS1 ( A) and the 5′–3′ Frame 1 of ENST00000647969 . 1 ( B ). Coding regions are shaded in pink, with the start codon (ATG) and stop codons highlighted in yellow. ( C ) Predicted three-dimensional structures of the peptides encoded by the putative ORFs in HTRA1-AS1 and ENST00000647969 . 1 , generated using AlphaFold. The structures display alpha-helices and loop regions, with the amino acid change caused by SNP rs61871745 indicated in pink. In summary, our study identifies HTRA1-AS1 and its isoform ENST00000647969 . 1 as antisense lncRNAs overlapping ARMS2 and demonstrates their significant downregulation in AMD retinas. Their altered expression, stress responsiveness, and coding potential highlight new mechanistic pathways at the 10q26 locus. Pinpointing the causal variants and clarifying the potential regulatory and/or coding roles of HTRA1-AS1 will be important to resolve the long-standing debate surrounding the ARMS2/HTRA1 locus and may ultimately uncover new therapeutic opportunities for AMD. Data Availability All data produced in the present work are contained in the manuscript Contributors PWZ conceived the study, designed all experiments, and wrote the primary manuscript draft. SL performed the bioinformatic screening for trans-acting element binding. ZHW, WL, JW, SL, LF, JW, CAB, and JQ contributed substantially to experimental execution, data collection, and analysis. PWZ, SLM, and DJZ supervised the overall process of data acquisition, analysis, interpretation, and manuscript preparation. Declaration of Interests The authors declare no conflicts of interests. Data sharing The authors declare that all data generated or analysed during this study are included in this published article. Acknowledgement The authors thank Dr. James T. Handa for his insightful suggestions and discussions, and Dr. Jikui Shen for his valuable assistance in predicting the three-dimensional structures of the putative peptide coding regions using AlphaFold. This study was supported by NEI P30 EY001765 (Wilmer Core Grant, Microscopy Module), NEI R01EY020406 and NEI X01HG006605. Footnotes Contact Address: Wilmer Eye Institute, Johns Hopkins University School of Medicine, 400 N Broadway, Smith Building, Room 3027, Baltimore, Maryland, 21231, USA Reference 1. ↵ Wong WL , Su X , Li X , Cheung CMG , Klein R , Cheng CY , Wong TY . Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis . Lancet Glob Health . 2014 ; 2 ( 2 ): e106 – e116 . doi: 10.1016/S2214-109X(13)70145-1 . OpenUrl CrossRef 2. ↵ Rein DB , Wittenborn JS , Burke-Conte Z , Gulia R , Robalik T , Ehrlich JR , Lundeen EA , Flaxman AD . Prevalence of Age-Related Macular Degeneration in the US in 2019 . JAMA Ophthalmol . 2022 Dec 1; 140 ( 12 ): 1202 – 1208 . doi: 10.1001/jamaophthalmol.2022.4401 . PMID: 36326752 ; PMCID: PMC9634594 . OpenUrl CrossRef PubMed 3. ↵ Fritsche LG , Chen W , Schu M , et al ; AMD Gene Consortium. Seven new loci associated with age-related macular degeneration . Nat Genet . 2013 ; 45 ( 4 ): 433 – 439 . doi: 10.1038/ng.2578 . OpenUrl CrossRef PubMed 4. ↵ Nguyen J , Brantley MA Jr , Schwartz SG . Genetics and age-related macular degeneration: a practical review for clinicians . Front Biosci (Schol Ed) . 2024 ; 16 ( 1 ): 3 . doi: 10.31083/j.fbs1601003 . OpenUrl CrossRef PubMed 5. ↵ Bhumika , Bora NS , Bora PS . Genetic insights into age-related macular degeneration Biomedicines . 2024 ; 12 ( 7 ): 1479 . doi: 10.3390/biomedicines12071479 . OpenUrl CrossRef PubMed 6. ↵ Barberio J , Lally C , Kupelian V , Hardiman O , Flanders WD . Estimated familial amyotrophic lateral sclerosis proportion: a literature review and meta-analysis . Neurol Genet . 2023 ; 9 ( 6 ): e200109 . doi: 10.1212/NXG.0000000000200109 . OpenUrl Abstract / FREE Full Text 7. ↵ Nijs M , Van Damme P. The genetics of amyotrophic lateral sclerosis . Curr Opin Neurol . 2024 ; 37 ( 5 ): 560 – 569 . doi: 10.1097/WCO.0000000000001294 . OpenUrl CrossRef PubMed 8. Funayama M. Contribution of genetics to Parkinson’s disease and future prospects . Juntendo Med J . 2025 ; 71 ( 2 ): 76 – 81 . doi: 10.14789/ejmj.JMJ24-0052-P . OpenUrl CrossRef PubMed 9. Rawls A , Okun MS . Parkinson disease . Continuum (Minneap Minn) . 2025 ; 31 ( 4 ): 930 – 955 . doi: 10.1212/cont.0000000000001593 . OpenUrl CrossRef PubMed 10. ↵ Ulaganathan S , Pitchaimani A. Spontaneous and familial models of Alzheimer’s disease: challenges and advances in preclinical research . Life Sci . 2023 ; 328 : 121918 . doi: 10.1016/j.lfs.2023.121918 . OpenUrl CrossRef PubMed 11. ↵ Andrews SJ , Renton AE , Fulton-Howard B , Podlesny-Drabiniok A , Marcora E , Goate AM . The complex genetic architecture of Alzheimer’s disease: novel insights and future directions . EBioMedicine . 2023 ; 90 : 104511 . doi: 10.1016/j.ebiom.2023.104511 . OpenUrl CrossRef 12. ↵ Pan Y , Fu Y , Baird PN , Guymer RH , Das T , Iwata T. Exploring the contribution of ARMS2 and HTRA1 genetic risk factors in age-related macular degeneration . Prog Retin Eye Res . 2023 ; 97 : 101159 . doi: 10.1016/j.preteyeres.2022.101159 . OpenUrl CrossRef PubMed 13. ↵ Klein ML , Schultz DW , Edwards A , Matise TC , Rust K , Berselli CB , et al. Age-related macular degeneration: clinical features in a large family and linkage to chromosome 1q . Arch Ophthalmol . 1998 ; 116 : 1082 – 1088 . OpenUrl CrossRef PubMed Web of Science 14. ↵ Fritsche LG , Igl W , Bailey JNC , Grassmann F , Sengupta S , Bragg-Gresham JL , et al. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants . Nat Genet . 2016 ; 48 : 134 – 143 . OpenUrl CrossRef PubMed 15. ↵ Okamoto H , Umeda S , Obazawa M , Minami M , Noda T , Mizota A , et al. Complement factor H polymorphisms in Japanese population with age-related macular degeneration . Mol Vis . 2006 ; 12 : 156 – 158 . OpenUrl PubMed Web of Science 16. Gotoh N , Yamada R , Hiratani H , Renault V , Kuroiwa S , Monet M , et al. No association between complement factor H gene polymorphism and exudative age-related macular degeneration in Japanese . Hum Genet . 2006 ; 120 : 139 – 143 . doi: 10.1007/s00439-006-0187-0 . OpenUrl CrossRef PubMed Web of Science 17. ↵ Fuse N , Miyazawa A , Mengkegale M , Yoshida M , Wakusawa R , Abe T , Tamai M. Polymorphisms in complement factor H and hemicentin-1 genes in a Japanese population with dry-type age-related macular degeneration . Am J Ophthalmol . 2006 ; 142 : 1074 – 1076 . doi: 10.1016/j.ajo.2006.07.030 . OpenUrl CrossRef PubMed Web of Science 18. ↵ Curcio CA , Mullins RF , Stone EM , Goerdt L , Kar D , Gao L , et al. Genetic associations of rod- and cone-mediated vision in aging and age-related macular degeneration . Invest Ophthalmol Vis Sci . 2025 ; 66 ( 9 ): 50 . doi: 10.1167/iovs.66.9.50 . OpenUrl CrossRef 19. ↵ Pan Y , Fu Y , Baird PN , Guymer RH , Das T , Iwata T. Exploring the contribution of ARMS2 and HTRA1 genetic risk factors in age-related macular degeneration . Prog Retin Eye Res . 2023 ; 97 : 101159 . doi: 10.1016/j.preteyeres.2022.101159 . OpenUrl CrossRef PubMed 20. ↵ Wahlin KJ , Maruotti JA , Sripathi SR , Ball J , Angueyra JM , Kim C , et al. Photoreceptor outer segment-like structures in long-term 3D retinas from human pluripotent stem cells . Sci Rep . 2017 ; 7 ( 1 ): 766 . doi: 10.1038/s41598-017-00774-9 . OpenUrl CrossRef PubMed 21. ↵ Maruotti J , Wahlin K , Gorrell D , Bhutto I , Lutty G , Zack DJ . A simple and scalable process for the differentiation of retinal pigment epithelium from human pluripotent stem cells . Stem Cells Transl Med . 2013 May ; 2 ( 5 ): 341 – 54 . doi: 10.5966/sctm.2012-0106 . Epub 2013 Apr 12. PMID: 23585288 ; PMCID: PMC3667560 . OpenUrl CrossRef PubMed Web of Science 22. ↵ Wang J , Zibetti C , Shang P , Sripathi SR , Zhang PW , Cano M , et al. ATAC-seq analysis reveals a widespread decrease of chromatin accessibility in age-related macular degeneration . Nat Commun . 2018 ; 9 ( 1 ): 1364 . doi: 10.1038/s41467-018-03856-y . OpenUrl CrossRef PubMed 23. ↵ Merle DA , Sen M , Armento A , Stanton CM , Thee EF , Meester-Smoor MA , et al. 10q26 – The enigma in age-related macular degeneration . Prog Retin Eye Res . 2023 ; 96 : 101154 . doi: 10.1016/j.preteyeres.2022.101154 . OpenUrl CrossRef PubMed 24. ↵ Blasiak J , Hyttinen JMT , Szczepanska J , Pawlowska E , Kaarniranta K. Potential of long non-coding RNAs in age-related macular degeneration . Int J Mol Sci . 2021 ; 22 ( 17 ): 9178 . doi: 10.3390/ijms22179178 . OpenUrl CrossRef 25. ↵ Zhang R , Wang L , Li Y , Gui C , Pei Y , Zhou G. Roles and mechanisms of long non-coding RNAs in age-related macular degeneration . Heliyon . 2023 ; 9 ( 11 ): e22307 . doi: 10.1016/j.heliyon.2023.e22307 . OpenUrl CrossRef 26. ↵ Farashi S , Abbott CJ , Ansell BR , Wu Z , Altay L , Arnon E , et al. Genetic risk of reticular pseudodrusen in age-related macular degeneration: HTRA1/lncRNA BX842242.1 dominates, with no evidence for complement cascade involvement . medRxiv. Preprint posted online September 28, 2024 . doi: 10.1101/2024.09.26.24314339 . OpenUrl Abstract / FREE Full Text 27. ↵ Yang Z , Camp NJ , Sun H , Tong Z , Gibbs D , Cameron DJ , et al. A variant of the HTRA1 gene increases susceptibility to age-related macular degeneration . Science . 2006 ; 314 ( 5801 ): 992 – 993 . doi: 10.1126/science.1133811 . OpenUrl Abstract / FREE Full Text 28. ↵ Rehman S , Aziz E , Akhtar W , Ilyas M , Mahmood T. Structural and functional characteristics of plant proteinase inhibitor-II (PI-II) family . Biotechnol Lett . 2017 ; 39 ( 5 ): 647 – 666 . doi: 10.1007/s10529-017-2298-1 . OpenUrl CrossRef PubMed 29. ↵ Wiggans GR , Cooper TA , VanRaden PM , Van Tassell CP , Bickhart DM , Sonstegard TS . Increasing the number of single nucleotide polymorphisms used in genomic evaluation of dairy cattle . J Dairy Sci . 2016 ; 99 ( 6 ): 4504 – 4511 . doi: 10.3168/jds.2015-10456 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted November 06, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following HTRA1-AS1, an ARMS2-region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share HTRA1-AS1 , an ARMS2 -region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients Ping-Wu Zhang , Zi-He Wan , Sheng Liu , Jie Wang , Srinivasa Sripathi , Weifeng Li , Junyeop Ahn , Sean Li , Laura Fan , Cynthia A. Berlinicke , Jiang Qian , Shannath L. Merbs , Donald J. Zack medRxiv 2025.10.29.25338834; doi: https://doi.org/10.1101/2025.10.29.25338834 Share This Article: Copy Citation Tools HTRA1-AS1 , an ARMS2 -region long non-coding RNA, is downregulated in retinas of age-related macular degeneration patients Ping-Wu Zhang , Zi-He Wan , Sheng Liu , Jie Wang , Srinivasa Sripathi , Weifeng Li , Junyeop Ahn , Sean Li , Laura Fan , Cynthia A. Berlinicke , Jiang Qian , Shannath L. Merbs , Donald J. Zack medRxiv 2025.10.29.25338834; doi: https://doi.org/10.1101/2025.10.29.25338834 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Ophthalmology Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4411) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15205) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6574) Geriatric Medicine (666) Health Economics (994) Health Informatics (4511) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15903) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (666) Neurology (6573) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (968) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5422) Public and Global Health (9205) Radiology and Imaging (2191) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fea8ac50eebdfa9',t:'MTc3OTI3MTcyNg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();