Genetic differentiation of populations residing in areas of high malaria endemicity in India

Sinha, Swapnil; Arya, Varun; Agarwal, Sarita; Habib, Saman

doi:10.1007/s12041-009-0010-5

Cited by 9 publications

(6 citation statements)

References 12 publications

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“…The utility of an India-specific baseline variability has been demonstrated during pre-next-generation sequencing (NGS) days-in infectious diseases (e.g., malaria, HIV), pharmacogenomics studies, disease associations, and identification of at-risk populations for various neurological, cutaneous, and high-altitude adaptation-related disorders (Aggarwal et al, 2010(Aggarwal et al, , 2015Bhattacharjee et al, 2008;Biswas et al, 2007Biswas et al, , 2010Chaki et al, 2011;Giri et al, 2014;Grover et al, 2010;Gupta et al, 2007;P. Jha et al, 2012;Kanchan et al, 2015;Kumar et al, 2009;Sinha, Arya, Agarwal, & Habib, 2009;Sinha et al, 2008;Talwar et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, mitochondrial and Y chromosome haplogroup‐based studies have also helped in the characterization of the gene pool of diverse Indian populations (Bamshad et al, 2001; Borkar, Ahmad, Khan, & Agrawal, 2011; Kivisild et al, 2003; Majumder et al, 1999; Thanseem et al, 2006). The utility of an India‐specific baseline variability has been demonstrated during pre‐next‐generation sequencing (NGS) days—in infectious diseases (e.g., malaria, HIV), pharmacogenomics studies, disease associations, and identification of at‐risk populations for various neurological, cutaneous, and high‐altitude adaptation‐related disorders (Aggarwal et al, 2010, 2015; Bhattacharjee et al, 2008; Biswas et al, 2007, 2010; Chaki et al, 2011; Giri et al, 2014; Grover et al, 2010; Gupta et al, 2007; P. Jha et al, 2012; Kanchan et al, 2015; Kumar et al, 2009; Sinha, Arya, Agarwal, & Habib, 2009; Sinha et al, 2008; Talwar et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India

et al. 2020

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There have been concerted efforts toward cataloging rare and deleterious variants in different world populations using high-throughput genotyping and sequencingbased methods. The Indian population is underrepresented or its information with respect to clinically relevant variants is sparse in public data sets. The aim of this study was to estimate the burden of monogenic disease-causing variants in Indian populations. Toward this, we have assessed the frequency profile of monogenic phenotype-associated ClinVar variants. The study utilized a genotype data set (global screening array, Illumina) from 2795 individuals (multiple in-house genomics cohorts) representing diverse ethnic and geographically distinct Indian populations. Of the analyzed variants from Global Screening Array,~9% were found to be informative and were either not known earlier or underrepresented in public databases in terms of their frequencies. These variants were linked to disorders, namely inborn errors of metabolism, monogenic diabetes, hereditary cancers, and various other hereditary conditions. We have also shown that our study cohort is genetically a better representative of the Indian population than its representation in the 1000 Genome Project (South Asians). We have created a database, ClinIndb, linked to the Leiden Open Variation Database, to help clinicians and researchers in diagnosis, counseling, and development of appropriate genetic screening tools relevant to the Indian populations and Indians living abroad.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India

et al. 2020

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“…2,18 A study in India, showed that high frequency of FcγR2A exon4 AA genotype protected the Tharus, a population living in the foothills of the Himalayas, from falciparum malaria. 19…”

Section: Introductionmentioning

confidence: 99%

Polymorphisms and expression ofTLR4and9in malaria in two ethnic groups of Assam, northeast India

et al. 2012

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Infectious diseases have been postulated to play an important role in exerting pressure and in selection of TLR polymorphisms. Single nucelotide polymorphisms (SNPs) of TLR4 have been reported to show unique distributions in populations from Africa, Asia and Europe, and malaria is suggested to influence these patterns. In this context, we examined association of TLR polymorphisms with the risk of malaria in two ethnic groups-the Austro-Asiatics and Tibeto-Burmans-from malaria endemic districts of Assam to understand the influence of malaria in selection of TLRs in these genetically-distinct populations. TLR9 (T-1237C) mutation was positively associated with complicated (P = 0.001) and frequent (P = 0.035) malaria in Austro-Asiatics (relative risk = 0.595 95% CI: 0.479-0.836), but not in Tibeto-Burmans. Nonetheless, these alleles were not in Hardy-Weinberg Equilibrium in Tibeto-Burmans (P < 0.001). In contrast, the TLR9 1486T/C genotype was favourable where it was negatively associated with complicated malaria (Fishers exact P = 0.014). Sequencing data revealed that the two populations differed in nucleotide diversity of the TLR9 promoter region. Enhanced expression of TLR4 (P = 0.05), but not of TLR9, was associated with complicated malaria. Austro-Asiatics appeared to have accumulated favourable genotypes of TLR9, perhaps because of their longer exposure to malaria.

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“…The contrast is particularly striking for the central and Western Terai Tharu populations: Tharus in the Western Terai region in Nepal have both sickle cell (0.05) and a high frequency of α + thalassaemia (0.72), but Central Terai Tharus have an α + thal frequency of 0.83 and no sickle cell at all (Modiano et al 1991). Indian Tharus from the Terai region of Uttar Pradesh have near-fixation of α + , at a frequency of 0.94 (Sinha et al 2009) as well as sickle cell. In this article, we extend the modelling work carried out in Williams et al (2005c) and Penman et al (2009) to ask whether these data from South Asia can be reconciled with the negative epistasis between α + thalassaemia and sickle cell documented in Africa.…”

Section: Onlineopen Termsmentioning

confidence: 99%

Negative Epistasis Between Α+ Thalassaemia and Sickle Cell Trait Can Explain Interpopulation Variation in South Asia

et al. 2011

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Recent studies in Kenya and Ghana have shown that individuals who inherit two malaria-protective genetic disorders of haemoglobin—α+ thalassaemia and sickle cell trait—experience a much lower level of malaria protection than those who inherit sickle cell trait alone. We have previously demonstrated that this can limit the frequency of α+ thalassaemia in a population in which sickle cell is present, which may account for the frequency of α+ thalassaemia in sub-Saharan Africa not exceeding 50%. Here we consider the relationship between α+ thalassaemia and sickle cell in South Asian populations, and show that very high levels of α+ thalassaemia combined with varying levels of malaria selection can explain why sickle cell has penetrated certain South Asian populations but not others.

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Genetic differentiation of populations residing in areas of high malaria endemicity in India

Cited by 9 publications

References 12 publications

Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India

Frequency spectrum of rare and clinically relevant markers in multiethnic Indian populations (ClinIndb): A resource for genomic medicine in India

Polymorphisms and expression ofTLR4and9in malaria in two ethnic groups of Assam, northeast India

Negative Epistasis Between Α+ Thalassaemia and Sickle Cell Trait Can Explain Interpopulation Variation in South Asia

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