Biology subjects

Nandakumar, P.

Publications and source records attributed to Nandakumar, P..

5 recordsLinked to original sources

bioRxiv2020

Multiple, independent, common variants overlapping known and putative gut enhancers at RET, SEMA3 and NRG1 underlie Hirschsprung disease risk in European ancestry subjects

PurposeHirschsprung disease (HSCR) is a developmental disorder of the enteric nervous system (ENS) characterized by congenital aganglionosis, and where individual cases harbor coding risk variants in ENS genes. Low-penetrance, common, noncoding variants at RET, SEMA3 and NRG1 loci have been associated in HSCR as well, implicating variable gene expression mediated by cis-regulatory element (CRE) variants as the causal mechanism. However, the extent and combinatorial effects of all putative CRE variants within and across these loci on HSCR is unknown. MethodsUsing 583 HSCR subjects, one of the largest samples of European ancestry studied, and genotyping 56 tag variants we evaluated association of all common variants overlapping putative gut CREs and fine-mapped variants at RET, SEMA3 and NRG1. ResultsWe demonstrate that 28 and 8 tag variants, several of which are independent, overlapping putative-enhancers at the RET and SEMA3 loci, respectively, and, 2 fine-mapped tag variants at NRG1 locus, are associated with HSCR. We demonstrate that risk increases with increasing risk allele dosage from multiple variants within and across these loci and varies >25- fold. ConclusionGene regulatory networks in HSCR-relevant cell types quantify the total burden of risk alleles through sensing reduced gene expression of multiple genes on disease.

genetics↗

bioRxiv2020

Genetic analyses identify widespread sex-differential participation bias

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of this participation bias is challenging as it requires the genotypes of unseen individuals. However, we demonstrate that it is possible to estimate comparative biases by performing GWAS contrasting one subgroup versus another. For example, we show that sex exhibits autosomal heritability in the presence of sex-differential participation bias. By performing a GWAS of sex in ~3.3 million males and females, we identify over 158 autosomal loci significantly associated with sex and highlight complex traits underpinning differences in study participation between sexes. For example, the body mass index (BMI) increasing allele at the FTO locus was observed at higher frequency in males compared to females (OR 1.02 [1.02-1.03], P=4.4x10-36). Finally, we demonstrate how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.

genetics↗

bioRxiv2019

Analysis of putative cis-regulatory elements regulating blood pressure variation

Hundreds of loci have been associated with blood pressure traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in [~]100,000 Genetic Epidemiology Research on Aging (GERA) study participants. In the present study, we subsequently focused on determining putative regulatory regions for these and other tissues of relevance to blood pressure, to both fine-map these loci by pinpointing genes and variants of functional interest within them, and to identify any novel genes.\n\nWe constructed maps of putative cis-regulatory elements using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Sequence variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. In order to identify genes of interest, we aggregate these variants in these putative cis-regulatory elements within 50Kb of the start or end of genes considered as \"expressed\" in these tissues or cell types using publicly available gene expression data, and use the deltaSVM scores as weights in the well-known group-wise sequence kernel association test (SKAT). We test for association with both blood pressure traits as well as expression within these tissues or cell types of interest, and identify several genes, including MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B, and PPCDC. Although our study centers on blood pressure traits, we additionally examined two known genes, SCN5A and NOS1AP involved in the cardiac trait QT interval, in the Atherosclerosis Risk in Communities Study (ARIC), as a positive control, and observed an expected heart-specific effect. Thus, our method may be used to identify variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.\n\nAuthor SummarySequence change in genes (\"variants\") are linked to the presence and severity of different traits or diseases. However, as genes may be expressed in different tissues and at different times and degrees, using this information is expected to more accurately identify genes of interest. Variants within the genes are essential, but also in the sequences (\"regulatory elements\") that control the genes expression in different tissues or cell types. In this study, we aim to use this information about expression and variants potentially involved in gene expression regulation to better pinpoint genes and variants in regulatory elements of interest for blood pressure regulation. We do so by taking advantage of such data that are publicly available, and use methods to combine information about variants in aggregate within a genes putative regulatory elements in tissues thought to be relevant for blood pressure, and identify several genes, meant to enable experimental follow-up.

genomics↗

bioRxiv2019

The gastrointestinal development ‘parts list’: transcript profiling of embryonic gut development in wildtype and Ret-deficient mice

The development of the gut from endodermal tissue to an organ with multiple distinct structures and functions occurs over a prolonged time during embryonic days E10.5-E14.5 in the mouse. During this process, one major event is innervation of the gut by enteric neural crest cells (ENCC) to establish the enteric nervous system (ENS). To understand the molecular processes underpinning gut and ENS development, we generated RNA-seq profiles from wildtype mouse guts at E10.5, E12.5 and E14.5 from both sexes. We also generated these profiles from homozygous Ret null embryos, a model for Hirschsprung disease (HSCR), in whom the ENS is absent. These data reveal four major features: (1) between E10.5 to E14.5 the developmental genetic programs change from expression of major transcription factors (TF) and its modifiers to genes controlling tissue (epithelium, muscle, endothelium) specialization; (2) the major effect of Ret is not only on ENCC differentiation to enteric neurons but also on the enteric mesenchyme and epithelium; (3) a muscle genetic program exerts significant effects on ENS development, and (4) sex differences in gut development profiles are minor. The genetic programs identified, and their changes across development, suggests that both cell autonomous and non-autonomous factors, and interactions between the different developing gut tissues, are important for normal ENS development and its disorders.\n\nSignificance statementThe mammalian gut is a complex set of tissues formed during development by orchestrating the timing of expression of many genes. Here we uncover the identity of these genes, their pathways and how they change during gut organogenesis. We used RNA-seq profiling in the wildtype mouse gut in both sexes during development (E10.5 - E14.5), as well as in a Ret null mouse, a model of Hirschsprung disease (HSCR). These studies have allowed us to expand the universe of genes and developmental processes that contribute to enteric neuronal innervation and to its dysregulation in disease.

genetics↗

bioRxiv2019

Insight into the genetic aetiology of retinal detachment by combining small clinical and large population-based datasets

Idiopathic retinal detachment is a serious common condition, but genetic studies to date have been hampered by the small size of the assembled cohorts. Genetic correlations between retinal detachment and high myopia or cataract operation were high, respectively 0.46 (SE=0.08) and 0.44 (SE=0.07), in the UK Biobank dataset and in line with known epidemiological associations. Meta-analysis of genome-wide association studies using UK Biobank retinal detachment cases (N=3977) and two cohorts, each comprising [~]1000 rhegmatogenous retinal detachment patients, uncovered 11 genome-wide significant association signals, near or within ZC3H11B, BMP3, COL22A1, DLG5, PLCE1, EFEMP2, TYR, FAT3, TRIM29, COL2A1 and LOXL1. Replication in the 23andMe dataset, where retinal detachment is self-reported by participants, firmly establishes association at six loci FAT3, COL22A1, TYR, BMP3, ZC3H11B and PLCE1. The former two seem to particularly impact on retinal detachment, the latter three shed light on shared aetiologies with cataract, myopia and glaucoma.\n\nAuthor SummaryRetinal detachments are common conditions that may lead to permanent severe sight reduction or blindness; they are a major cause of emergency eye surgery. The most common type of retinal detachment follows a break in the retina and is thought to be in part genetically determined but little is known about the contributing individual genetic risk variants. The condition prevalence increases with age and with common eye conditions such as myopia, cataract or glaucoma. We showed that the retinal detachment cases derived from self-report or hospitalisation records in the large UK Biobank dataset show very similar characteristics to samples of carefully clinically evaluated retinal detachment with break cases and therefore could be used to perform genetic analysis of the condition. Association studies require large sample of cases and by pooling Biobank and clinical cases, this study identifies 11 novel significant associations, six of which were further replicated in an independent population-based dataset (23andMe). Two of the replicated findings seem to specifically underline retinal detachment risk while three others highlight shared genetic risk with myopia, cataract and/or glaucoma, paving the way to better understanding of these conditions and of their overlap.

genetics↗