Description of Research Expertise
Genome wide association studies of age-related macular degeneration and glaucoma; Next-generation targeted sequencing of age-related macular degeneration in African Americans; Genetics of age-related macular degeneration in the Amish; Whole exome sequencing of families with refractive error; Zebrafish modeling of refractive error and glaucoma; Characterization of mouse models for microphthalmia.
Key Words: Fun Lab, Bioinformatics galore, espirit de corps, collegial atmosphere, challenging projects, molecular genetics.
Description of Research:
Age-related macular degeneration (AMD) in African Americans
Much work has been accomplished on the genetics of AMD in Caucasians to the point that we currently have 10 well-defined loci identified by genome-wide association studies. While we have had amazing successes in Caucasians for AMD, very little has been done in African Americans probably because the disease is much rarer in this group. A GWAS study is not plausible in African Americans because of the decreased frequency of AMD. Therefore, we are using new DNA sequencing technology to identify the reasons that AMD is less severe in African Americans. We have collected a large cohort of African American cases and controls and are currently utilizing targeted next-gen sequencing to identify protective haplotypes that might offer an explanation of resistance to AMD development in African Americans. If these protective SNPs are found, they could serve as new potential drug targets.
Expression differences between normal and AMD eyes
We have been very successful in the identification of susceptibility genes for AMD through GWAS. The next horizon is to understand the expression differences between eyes with AMD and eyes that are normal. To identify differential expression between normal and AMD eyes, we have collected a series of postmortem eyes with and without AMD. RNA and DNA has been isolated from these eyes for the purpose of RNA sequencing and genotyping. Our underlying hypothesis is that there is a difference in normal transcript expression between normal and AMD eyes or a defect in alternative splicing that predisposes to AMD. The RNA-Seq data is being analyzed for expression differences as well as for alternative splicing defects with our new algorithm developed in the lab, SplicePL. Expression will also be correlated with known AMD risk SNPs to assess SNP potential to influence expression.
Genetics of AMD in the Amish
The genetics of AMD has been well studied in unrelated case-control Caucasian cohorts. However, very little has been done to identify genes in families. To that end, we have screened 3000 Amish individuals over the age of 50 years living in Lancaster County, Pa for various eye diseases including AMD. Every subject visiting the Amish clinic received a full eye exam, an epidemiology questionnaire, and a fundus photo along with the donation of a blood sample. We currently have DNA on all these individuals. Our collected Amish cohort currently consists of 750 nuclear families and has tremendous power to identify rare variants. We are currently preparing to do whole exome sequencing in selected families for the purpose of rare variant discovery in AMD. Discovery of rare AMD variants of large effect will have potential impact in the general population.
Genetics of Refractive Error
Refractive error is an abnormality of the eye that results in myopia, hyperopia or astigmatism. It is the leading cause of blindness worldwide. Most studies to date have centered on family linkage studies. Our lab is currently leading an international consortium to identify the genes for refractive error through GWAS and next-gen sequencing. We have just completed a GWAS of 7000 individuals with a few significant hits. We now seek to understand how these significant GWAS SNPs lead to the development of refractive error. We are currently utilizing bioinformatic tools to characterize the function of these SNPS and will move to functional studies in zebrafish after exhausting our bioinformatic tools. In addition, we have collected DNA from large families transmitting myopia and are preparing to perform whole exome sequencing to identify rare variants in these families.
Modeling of Human Disease in Zebrafish
We have developed a system in the lab to assess the refractive error phenotype in zebrafish embryos. Current experiments include knockdown and overexpression of various potential refractive error genes as a validation to the GWAS hits we have identified. Validated results in a zebrafish model will be followed by RNA-Seq of the mutants to provide a framework for a systems biology approach to understanding refractive error.
Characterization of Mouse Models for Microphthalmia
Over the past few years we have been characterizing a mouse model for microphthalmia (Tcm), a phenotype identified in a colony of X-ray irradiated mouse. Genetic mapping refined the causative locus to a 1.3Mb region on mouse Chromosome 4 which contains 5 genes. Further molecular characterization is underway in our lab to identify the founder mutation responsible for the microphthalmic phenotype.
Common techniques in the lab include bioinformatics, DNA cloning, PCR, agarose gel electrophoresis, in situ hybridization, DNA sequencing and library screening.
Sterling JK, Baumann B, Foshe S, Voigt A, Guttha S, Alnemri A, McCright SJ, Li M, Zauhar RJ, Montezuma SR, Kapphahn RJ, Chavali VRM, Hill DA, Ferrington DA, Stambolian D, Mullins RF, Merrick D, Dunaief JL.: Inflammatory adipose activates a nutritional immunity pathway leading to retinal dysfunction Cell Rep 39 : 110942,2022.
Oncel D, Manafi N, Nittala MG, Velaga SB, Stambolian D, Pericak-Vance MA, Haines JL, Sadda SR.: Effect of OCT B-scan density on sensitivity for detection of intraretinal hyperreflective foci in eyes with age-related macular degeneration Curr Eye Res : 2022.
Corvi F, Corradetti G, Nittala MG, Velaga SB, Haines JL, Pericak-Vance MA, Stambolian D, Sadda SR.: COMPARISON OF SPECTRALIS AND CIRRUS OPTICAL COHERENCE TOMOGRAPHY FOR THE DETECTION OF INCOMPLETE AND COMPLETE RETINAL PIGMENT EPITHELIUM AND OUTER RETINAL ATROPHY Retina 41 : 1851-1857,2021.
Lyu Y, Zauhar R, Dana N, Strang CE, Hu J, Wang K, Liu S, Pan N, Gamlin P, Kimble JA, Messinger JD, Curcio CA, Stambolian D, Li M.: Implication of specific retinal cell-type involvement and gene expression changes in AMD progression using integrative analysis of single-cell and bulk RNA-seq profiling Sci Rep 11 : 15612,2021.
Simpson CL, Musolf AM, Cordero RY, Cordero JB, Portas L, Murgia F, Lewis DD, Middlebrooks CD, Ciner EB, Bailey-Wilson JE, Stambolian D.: Myopia in African Americans Is Significantly Linked to Chromosome 7p15.2-14.2 Invest Ophthalmol Vis Sci 62 : 16,2021.
Tideman JWL, Pärssinen O, Haarman AEG, Khawaja AP, Wedenoja J, Williams KM, Biino G, Ding X, Kähönen M, Lehtimäki T, Raitakari OT, Cheng CY, Jonas JB, Young TL, Bailey-Wilson JE, Rahi J, Williams C, He M, Mackey DA, Guggenheim JA; UK Biobank Eye and Vision Consortium and the Consortium for Refractive Error and Myopia (CREAM Consortium).: Evaluation of Shared Genetic Susceptibility to High and Low Myopia and Hyperopia JAMA Ophthalmol 139 : 601-609,2021.
Rakocz N, Chiang JN, Nittala MG, Corradetti G, Tiosano L, Velaga S, Thompson M, Hill BL, Sankararaman S, Haines JL, Pericak-Vance MA, Stambolian D, Sadda SR, Halperin E.: Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging NPJ Digit Med 4 : 44,2021.
Corvi F, Srinivas S, Nittala MG, Corradetti G, Velaga SB, Stambolian D, Haines J, Pericak-Vance MA, Sadda SR.: Reproducibility of qualitative assessment of drusen volume in eyes with age related macular degeneration Eye (Lond) : 2021.
Strunz T, Lauwen S, Kiel C; International AMD Genomics Consortium (IAMDGC), Hollander AD, Weber BHF: A transcriptome-wide association study based on 27 tissues identifies 106 genes potentially relevant for disease pathology in age-related macular degeneration Sci Rep. 10 (1): 1584,2020.
Li, Xiangjie; Wang, Kui; Lyu, Yafei; Pan, Huize; Zhang, Jingxiao; Stambolian, Dwight; Susztak, Katalin; Reilly, Muredach P; Hu, Gang; Li, Mingyao.: Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis. Nature communications 11 (1): 2338,2020.
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Academic Contact Information
Rm. 313 Stellar-Chance Labs
422 Curie Boulevard
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