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  4. Assessment of CFH and HTRA1 polymorphisms in age-related macular degeneration using classic and machine-learning approaches
 
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Assessment of CFH and HTRA1 polymorphisms in age-related macular degeneration using classic and machine-learning approaches

Journal
Ophthalmic Genetics
ISSN
1381-6810
1744-5094
Date Issued
2020
Author(s)
Martínez Velasco, Antonieta Teodora  orcid-logo
Facultad de Ingeniería - CampCM  
Antonio-Aguirre, Bani
Facultad de Ciencias de la Salud - CampCM  
Martinez-Villaseñor, Lourdes  
Facultad de Ingeniería - CampCM  
Palacio-Pastrana, Claudia
Facultad de Ingeniería - CampCM  
Lira, Esmeralda  
Zenteno, Juan Carlos
Facultad de Ciencias de la Salud - CampCM  
Ramírez-Sánchez, Israel
Zepeda-Palacio, Claudia
Facultad de Ingeniería - CampCM  
Mendoza Vera, Cristina Azucena
Camacho-Ordóñez, Azyadeh
Ortiz Bibriesca, Daniela
Estrada Mena, Francisco Javier  
Facultad de Ingeniería - CampCM  
Type
Resource Types::text::journal::journal article
DOI
10.1080/13816810.2020.1804945
URL
https://scripta.up.edu.mx/handle/123456789/2128
Abstract
CFH: and HTRA1 are pivotal genes driving increased risk for age-related macular degeneration (AMD) among several populations. Here, we performed a hospital-based case-control study to evaluate the effects of three single nucleotide polymorphisms (SNPs) among Hispanics from Mexico. Materials and methods: 122 cases and 249 controls were genotyped using Taqman probes. Experienced ophthalmologists diagnosed AMD following the American Association of Ophthalmology guidelines. We studied CFH (rs1329428, rs203687) and HTRA1 (rs11200638) SNPs thoroughly by logistic regression models (assuming different modes of inheritance) and machine learning-based methods (ML). HTRA1: rs11200638 is the most significant polymorphism associated with AMD in our studied population. In a multivariate regression model adjusted for clinically and statistically meaningful covariates, the A/G and A/A genotypes increased the odds of disease by a factor of 2.32 and 7.81, respectively (P < .05) suggesting a multiplicative effect of the polymorphic A allele. Furthermore, this observation remains statistically meaningful in the allelic, dominant, and recessive models, and ML algorithms. When stratifying by phenotype, this polymorphism was significantly associated with increased odds for geographic atrophy (GA) in a recessive mode of inheritance (12.4, p < .05). Conclusions: In sum, this work supports a strong association between HTRA1 genetic variants and AMD in Hispanics from Mexico, especially with GA. Moreover, ML was able to replicate the results of conventional biostatistics methods unbiasedly. © 2020 Taylor & Francis Group, LLC.

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