Human Metabolic Individuality in Biomedical and Pharmaceutical Research

Prakash, Siddharth K.

doi:10.1161/circgenetics.111.962175

Cited by 6 publications

(4 citation statements)

References 39 publications

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“…Variation in metabolite levels constitutes one of the major causes of variations in trait manifestation (Prakash, ; Saito, ; Chen et al ., ). It is highly likely that many of the mQTLs would be the causes of phenotypic change.…”

Section: Resultsmentioning

confidence: 97%

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Wang

Gong

et al. 2019

The Plant Journal

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Plants are considered an important food and nutrition source for humans. Despite advances in plant seed metabolomics, knowledge about the genetic and molecular bases of rice seed metabolomes at different developmental stages is still limited. Here, using Zhenshan 97 (ZS97) and Minghui 63 (MH63), we performed a widely targeted metabolic profiling in seeds during grain filling, mature seeds and germinating seeds. The diversity between MH63 and ZS97 was characterized in terms of the content of metabolites and the metabolic shifting across developmental stages. Taking advantage of the ultra-high-density genetic map of a population of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, we identified 4681 putative metabolic quantitative trait loci (mQTLs) in seeds across the three stages. Further analysis of the mQTLs for the codetected metabolites across the three stages revealed that the genetic regulation of metabolite accumulation was closely related to developmental stage. Using in silico analyses, we characterized 35 candidate genes responsible for 30 structurally identified or annotated compounds, among which LOC_Os07g04970 and LOC_Os06g03990 were identified to be responsible for feruloylserotonin and L-asparagine content variation across populations, respectively. MetaboliteÀagronomic trait association and colocation between mQTLs and phenotypic quantitative trait loci (pQTLs) revealed the complexity of the metaboliteÀagronomic trait relationship and the corresponding genetic basis.

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Section: Resultsmentioning

confidence: 97%

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Wang

Gong

et al. 2019

The Plant Journal

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“…Of the twenty mQTL-associated CSF metabolites that were mapped to known metabolite names, thirteen (65%) have been previously detected in QTL studies on CSF 13 (n=5), blood [2][3][4] (n=10), saliva 5 (n=3) or urine 6 (n=3) metabolite levels (Figure S1, matched by metabolite then for SNPs in LD R2>0.8).…”

Section: Qtl Mapping Of Csf Metabolites Identifies Novel and Validate...mentioning

confidence: 99%

“…1 The study of metabolomics in particular allows the detection of small changes in endogenous and exogenous compounds, thereby closely reflecting the current physiological state of cells, tissue or organisms. [2][3][4][5][6] Due to the relative inaccessibility of in vivo brain tissue and its surroundings, (early) insights into biological processes underlying psychiatric and neurodegenerative disorders have been limited. 7,8 Cerebrospinal fluid (CSF) is in close contact with the brain, and is important for providing nutrients and participates in waste removal of neural metabolism through interaction with interstitial fluid surrounding brain cells.…”

Section: Introductionmentioning

confidence: 99%

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Reus,

Boltz,

Francia

et al. 2023

Preprint

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Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanismsin vivo, measuring 5,543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n=490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n=487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders, we performed a metabolome-wide association study (MWAS), identifying 40 associations between CSF metabolites and brain traits. Similarly, over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.

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“…To our knowledge mQTL analyses have never been conducted in any organism, although genome-wide association studies combined with metabolic profiling were conducted in a recent human study (Prakash, 2011; Suhre et al, 2011). The human study identified 37 genetic loci associated with blood metabolite concentrations, of which 25 showed effect sizes of 10–60% which is extraordinarily high for genome-wide association studies (Prakash, 2011; Suhre et al, 2011). …”

Section: Future Studies In Drosophila Neurotoxicologymentioning

confidence: 99%

Drosophila melanogaster as a model for lead neurotoxicology and toxicogenomics research

Hirsch¹,

Lnenicka²,

Possidente³

et al. 2012

Front. Gene.

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Drosophila melanogaster is an excellent model animal for studying the neurotoxicology of lead. It has been known since ancient Roman times that long-term exposure to low levels of lead results in behavioral abnormalities, such as what is now known as attention deficit hyperactivity disorder (ADHD). Because lead alters mechanisms that underlie developmental neuronal plasticity, chronic exposure of children, even at blood lead levels below the current CDC community action level (10 μg/dl), can result in reduced cognitive ability, increased likelihood of delinquency, behaviors associated with ADHD, changes in activity level, altered sensory function, delayed onset of sexual maturity in girls, and changes in immune function. In order to better understand how lead affects neuronal plasticity, we will describe recent findings from a Drosophila behavioral genetics laboratory, a Drosophila neurophysiology laboratory, and a Drosophila quantitative genetics laboratory who have joined forces to study the effects of lead on the Drosophila nervous system. Studying the effects of lead on Drosophila nervous system development will give us a better understanding of the mechanisms of Pb neurotoxicity in the developing human nervous system.

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Human Metabolic Individuality in Biomedical and Pharmaceutical Research

Cited by 6 publications

References 39 publications

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Drosophila melanogaster as a model for lead neurotoxicology and toxicogenomics research

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