Saeideh Khodaee

University of Tehran

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H. R. Monsef‐Esfahani

Tehran University of Medical Sciences

Sabbir Ansari

National Institute of Cholera and Enteric Diseases

Maryam Moghimi

Shomal University

Dan Vitale

Data Tecnica International (United States)

Cornelis Blauwendraat

National Institutes of Health

Brian Fiske

Michael J. Fox Foundation

Pettarusp M. Wadia

Jaslok Hospital

Sindhuja Mohareer

Niraj Kumar

All India Institute of Medical Sciences

Ashwin Ashok Kumar Sreelatha

University of Tübingen

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Sree Chitra Thirunal Institute for Medical Sciences and Technology

All India Institute of Medical Sciences

Institute of Medical Sciences

University of Tehran

All India Institute of Medical Sciences Bhopal

All India Institute of Medical Sciences Raipur

John Wiley & Sons (United States)

Tehran University of Medical Sciences

Creative Commons

National Institute of Mental Health and Neurosciences

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Deciphering the Genetic Architecture of Parkinsons Disease in India

medRxiv (Cold Spring Harbor Laboratory) (2025)

Asha Kishore Ashwin Ashok Kumar Sreelatha Amabel Tenghe Rupam Borgohain Divya Kalikavil Puthanveedu

The genomic landscape of the Indian population, particularly for age-related disorders like Parkinsons disease (PD) remains underrepresented in global research. Genetic variability in PD has been studied predominantly in European populations, offering limited insights into its role within the Indian population. To address this gap, we conducted the first pan-India genomic survey of PD involving 4,806 cases and 6,364 controls, complemented by a meta-analysis integrating summary statistics from a multi-ancestry PD meta-analysis (N=611,485). We further leveraged RNA-sequencing data from lymphoblastoid cell lines of 731 individuals from the 1000 Genomes project to evaluate the expression of key loci across global populations. Our findings reveal a higher genetic burden of PD in the Indian population compared to Europeans, accounting for ~30% of the previously unexplained heritability. Thirteen genome-wide significant loci were identified, including two novel loci, with an additional three loci uncovered through meta-analysis. Polygenic risk score analysis showed moderate transferability from European populations. Our results highlight the importance of genetic loci in immune function, lipid metabolism and SNCA aggregation in PD pathogenesis, with gene expression variability emphasizing population-specific differences. We also established South Asias largest PD biobank, providing a foundation for patient-centric approaches to PD research and treatment in India.

Genetic architecture

10.1101/2025.02.17.25322132

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Human APOBEC3 Variations and Viral Infection

Viruses (2021)

Shiva Sadeghpour Saeideh Khodaee Mostafa Rahnama Hamzeh Rahimi Diako Ebrahimi

Human APOBEC3 (apolipoprotein B mRNA-editing catalytic polypeptide-like 3) enzymes are capable of inhibiting a wide range of endogenous and exogenous viruses using deaminase and deaminase-independent mechanisms. These enzymes are essential components of our innate immune system, as evidenced by (a) their strong positive selection and expansion in primates, (b) the evolution of viral counter-defense mechanisms, such as proteasomal degradation mediated by HIV Vif, and (c) hypermutation and inactivation of a large number of integrated HIV-1 proviruses. Numerous APOBEC3 single nucleotide polymorphisms, haplotypes, and splice variants have been identified in humans. Several of these variants have been reported to be associated with differential antiviral immunity. This review focuses on the current knowledge in the field about these natural variations and their roles in infectious diseases.

APOBEC3G

10.3390/v13071366

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Chemical composition and antimicrobial activity of essential oils from Geum kokanicum

Chemistry of Natural Compounds (2008)

Mohammad Ali Faramarzi Maryam Moghimi H. R. Monsef‐Esfahani Ahmad Reza Shahverdi Saeideh Khodaee

10.1007/s10600-009-9211-7

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iMM1865: A New Reconstruction of Mouse Genome-Scale Metabolic Model

Scientific Reports (2020)

Saeideh Khodaee Yazdan Asgari Mehdi Totonchi Mohammad Hossein Karimi‐Jafari

Since the first in silico generation of a genome-scale metabolic (GSM) model for Haemophilus influenzae in 1999, the GSM models have been reconstructed for various organisms including human and mouse. There are two important strategies for generating a GSM model: in the bottom-up approach, individual genomic and biochemical components are integrated to build a GSM model. Alternatively, the orthology-based strategy uses a previously reconstructed model of a reference organism to infer a GSM model of a target organism. Following the update and development of the metabolic network of reference organism, the model of the target organism can also be updated to eliminate defects. Here, we presented iMM1865 model as an orthology-based reconstruction of a GSM model for Mus musculus based on the last flux-consistent version of the human metabolic network, Recon3D. We proposed two versions of the new mouse model, iMM1865 and min-iMM1865, with the same number of gene-associated reactions but different subsets of non-gene-associated reactions. A third extended but flux-inconsistent model (iMM3254) was also created based on the extended version of Recon3D. Compared to the previously published mouse models, both versions of iMM1865 include more comprehensive annotations of metabolites and reactions with no dead-end metabolites and blocked reactions. We evaluated functionality of the models using 431 metabolic objective functions. iMM1865 and min-iMM1865 passed 93% and 87% of the tests, respectively, while iMM1415 and MMR (another available mouse GSM) passed 80% and 84% of the tests, respectively. Three versions of tissue-specific embryo heart models were also reconstructed from each of iMM1865 and min-iMM1865 using mCADRE algorithm with different thresholds on expression-based scores. The ability of corresponding GSM and embryo heart models to predict essential genes was assessed across experimentally derived lethal and viable gene sets. Our analysis revealed that tissue-specific models render much better predictions than GSM models.

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GSM

Flux Balance Analysis

10.1038/s41598-020-63235-w

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Citations (28)