Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types
TL;DR: In this paper, the authors developed lymphoblastoid cell line (LCL) from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda.
Abstract: Differences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate molecular players for individualized and early interventions. Functional studies of lymphoblastoid cell line (LCL) model of phenotypically well-characterized healthy individuals can help deconvolute and validate these molecular mechanisms. In this study, LCLs are developed from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV were studied in these LCLs. Significant differences in cell proliferation rates were observed between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one of the fast growing groups (Vata) shows higher cell death but recovers its numbers due to an inherent higher rates of proliferation. This study reveals that baseline differences in cell proliferation could be a key to understanding the survivability of cells under UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitution types but can also help set priors during the design of an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes among healthy individuals with potential implications in precision medicine.
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TL;DR: It is hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types and highlight novel SNPs that could explain differential trajectories for immune response, bleeding or thrombosis.
Abstract: Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed “Prakriti”. It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.
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TL;DR: In this paper , the authors explored the differential response to orthostatic stress in different Prakriti types using HRV and found that Kapha group had lower baseline HRV than other two groups, although not statistically significant.
Abstract: Autonomic modulation is critical during various physiological activities, including orthostatic stimuli and primarily evaluated by heart rate variability (HRV). Orthostatic stress affects people differently suggesting the possibility of identification of predisposed groups to autonomic dysfunction‐related disorders in a healthy state. One way to understand this kind of variability is by using Ayurvedic approach that classifies healthy individuals into Prakriti types based on clinical phenotypes. To this end, we explored the differential response to orthostatic stress in different Prakriti types using HRV. HRV was measured in 379 subjects(Vata = 97, Pitta = 68, Kapha = 68, and Mixed Prakriti = 146) from two geographical regions(Vadu and Delhi NCR) for 5 min supine (baseline), 3 min head‐up‐tilt (HUT) at 60°, and 5 min resupine. We observed that Kapha group had lower baseline HRV than other two groups, although not statistically significant. The relative change (%Δ1&2) in various HRV parameters in response to HUT was although minimal in Kapha group. Kapha also had significantly lower change in HR, LF (nu), HF (nu), and LF/HF than Pitta in response to HUT. The relative change (%Δ1) in HR and parasympathetic parameters (RMSSD, HF, SD1) was significantly greater in the Vata than in the Kapha. Thus, the low baseline and lower response to HUT in Kapha and the maximum drop in parasympathetic activity of Vata may indicate a predisposition to early autonomic dysfunction and associated conditions. It emphasizes the critical role of Prakriti‐based phenotyping in stratifying the differential responses of cardiac autonomic modulation in various postures among healthy individuals across different populations.
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TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations
TL;DR: This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity and reveals extensive heteroallelic changes during healthy and disease states and an unexpected RNA editing mechanism.
1,142 citations
TL;DR: Phenomics should be recognized and pursued as an independent discipline to enable the development and adoption of high-throughput and high-dimensional phenotyping.
Abstract: A key goal of biology is to understand phenotypic characteristics, such as health, disease and evolutionary fitness. Phenotypic variation is produced through a complex web of interactions between genotype and environment, and such a 'genotype-phenotype' map is inaccessible without the detailed phenotypic data that allow these interactions to be studied. Despite this need, our ability to characterize phenomes - the full set of phenotypes of an individual - lags behind our ability to characterize genomes. Phenomics should be recognized and pursued as an independent discipline to enable the development and adoption of high-throughput and high-dimensional phenotyping.
1,104 citations
TL;DR: In this paper, the authors report analyses from a study of gene-environment interaction in adolescent depression using DNA from 377 adolescents, representing the four quadrants of high or low depression.
Abstract: We report analyses from a study of gene-environment interaction in adolescent depression. The sample was selected from 1990 adolescents aged 10-20 years: those with depression symptoms in the top or bottom 15% were identified and divided into high or low environmental risk groups. DNA was obtained from 377 adolescents, representing the four quadrants of high or low depression and high or low environmental risk. Markers within, or close to, each of the serotonergic genes 5HTT, HTR2A, HTR2C, MAOA (monoamine oxidase type A) and tryptophan hydroxylase (TPH) were genotyped. Environmental risk group was a nonsignificant predictor and sex was a significant predictor of the depression group. HTR2A and TPH significantly predicted the depression group, independent of the effects of sex, environmental risk group and their interaction. In addition, there was a trend for an effect of 5HTTLPR, which was significant in female subjects. Furthermore, there was a significant genotype-environmental risk interaction for 5HTTLPR in female subjects only, with the effect being in the same direction as another recent study, reaffirming that an important source of genetic heterogeneity is exposure to environmental risk.
619 citations
TL;DR: This protocol outlines the carboxyfluorescein diacetate succinimidyl ester (CFSE) method for following the proliferation of human and mouse lymphocytes both in vitro and in vivo, finding that division-dependent changes in the expression of cell-surface markers and intracellular proteins are easily quantified by flow cytometry.
Abstract: This protocol outlines the carboxyfluorescein diacetate succinimidyl ester (CFSE) method for following the proliferation of human lymphocytes in vitro and mouse lymphocytes both in vitro and in vivo. The method relies on the ability of CFSE to covalently label long-lived intracellular molecules with the highly fluorescent dye, carboxyfluorescein. Following each cell division, the equal distribution of these fluorescent molecules to progeny cells results in a halving of the fluorescence of daughter cells. The CFSE labeling protocol described, which typically takes <1 h to perform, allows the detection of up to eight cell divisions before CFSE fluorescence is decreased to the background fluorescence of unlabeled cells. Protocols are outlined for labeling large and small numbers of human and mouse lymphocytes, labeling conditions being identified that minimize CFSE toxicity but maximize the number of cell divisions detected. An important feature of the technique is that division-dependent changes in the expression of cell-surface markers and intracellular proteins are easily quantified by flow cytometry.
564 citations