Format

Send to

Choose Destination
Front Aging Neurosci. 2016 May 23;8:115. doi: 10.3389/fnagi.2016.00115. eCollection 2016.

AMD Genetics in India: The Missing Links.

Author information

1
Neuroscience Research Lab, Department of Neurology, Post Graduate Institute of Medical Education and Research Chandigarh, India.
2
Neuroscience Research Lab, Department of Neurology, Post Graduate Institute of Medical Education and Research Chandigarh, India; Centre for Systems Biology and Bioinformatics, Panjab UniversityChandigarh, India.
3
Centre for Systems Biology and Bioinformatics, Panjab UniversityChandigarh, India; Department of Statistics, Panjab UniversityChandigarh, India.
4
Advanced Eye Centre, Post Graduate Institute of Medical Education and Research Chandigarh, India.
5
Neurobiology Neurodegeneration and Repair Laboratory, National Eye Institute Bethesda, MD, USA.
6
Institute of BioinformaticsBangalore, India; YU-IOB Center for Systems Biology and Molecular Medicine, Yenepoya UniversityMangalore, India; NIMHANS-IOB Proteomics and Bioinformatics Laboratory, Neurobiology Research Centre, National Institute of Mental Health and NeurosciencesBangalore, India.

Abstract

Age related macular degeneration is a disease which occurs in aged individuals. There are various changes that occur at the cellular, molecular and physiological level with advancing age (Samiec et al., 1988; Sharma K. et al., 2014). Drusen deposition between retinal pigment epithelium (RPE) and Bruch's membrane (BM) is one of the key features in AMD patients (Mullins et al., 2000; Hageman et al., 2001) similar to Aβ/tau aggregates in Alzheimer's disease (AD) patients. The primary goal of this review is to discuss whether the various candidate genes and associated biomarkers, that are known to play an independent role in progression of AMD, exert deleterious effect on phenotype, alone or in combination, in Indian AMD patients from the same ethnic group and the significance of such research. A statistical model for probable interaction between genes could be derived from such analysis. Therefore, one can use multiple modalities to identify and enrol AMD patients based on established clinical criteria and examine the risk factors to determine if these genes are associated with risk factors, biomarkers or disease by Mendelian randomization. Similarly, there are large numbers of single nucleotide polymorphisms (SNPs) identified in human population. Even non-synonymous SNPs (nsSNPs) are believed to induce deleterious effects on the functionality of various proteins. The study of such snSNPs could provide a better genetic insight for diverse phenotypes of AMD patients, predicting significant risk factors for the disease in Indian population. Therefore, the prediction of biological effect of nsSNPs in the candidate genes and the associated grant applications in the subject are highly solicited.Therefore, genotyping and levels of protein expression of various genes would provide wider canvas in genetic complexity of AMD pathology which should be evaluated by valid statistical and bioinformatics' tools. Longitudinal follow up of Indian AMD patients to evaluate the temporal effect of SNPs and biomarkers on progression of disease would provide a unique strategy in the field.

KEYWORDS:

Mendelian randomization; SNP; age related macular degeneration; bio-informatics analysis; biomarkers; longitudinal analysis; snSNPs; statistical modeling

Supplemental Content

Full text links

Icon for Frontiers Media SA Icon for PubMed Central
Loading ...
Support Center