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Srivastava, Gyan

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Srivastava

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Gyan

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Srivastava, Gyan
Author's Publications: search.filters.isAuthorOfPublication.62d74f3d-06b0-47ec-bf95-ba197c001fb4

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    24-Hour Rhythms of DNA Methylation and Their Relation with Rhythms of RNA Expression in the Human Dorsolateral Prefrontal Cortex
    (Public Library of Science, 2014) Lim, Andrew S. P.; Srivastava, Gyan; Yu, Lei; Chibnik, Lori; Xu, Jishu; Buchman, Aron S.; Schneider, Julie A.; Myers, Amanda J.; Bennett, David A.; De Jager, Philip
    Circadian rhythms modulate the biology of many human tissues, including brain tissues, and are driven by a near 24-hour transcriptional feedback loop. These rhythms are paralleled by 24-hour rhythms of large portions of the transcriptome. The role of dynamic DNA methylation in influencing these rhythms is uncertain. While recent work in Neurospora suggests that dynamic site-specific circadian rhythms of DNA methylation may play a role in modulating the fungal molecular clock, such rhythms and their relationship to RNA expression have not, to our knowledge, been elucidated in mammalian tissues, including human brain tissues. We hypothesized that 24-hour rhythms of DNA methylation exist in the human brain, and play a role in driving 24-hour rhythms of RNA expression. We analyzed DNA methylation levels in post-mortem human dorsolateral prefrontal cortex samples from 738 subjects. We assessed for 24-hour rhythmicity of 420,132 DNA methylation sites throughout the genome by considering methylation levels as a function of clock time of death and parameterizing these data using cosine functions. We determined global statistical significance by permutation. We then related rhythms of DNA methylation with rhythms of RNA expression determined by RNA sequencing. We found evidence of significant 24-hour rhythmicity of DNA methylation. Regions near transcription start sites were enriched for high-amplitude rhythmic DNA methylation sites, which were in turn time locked to 24-hour rhythms of RNA expression of nearby genes, with the nadir of methylation preceding peak transcript expression by 1–3 hours. Weak ante-mortem rest-activity rhythms were associated with lower amplitude DNA methylation rhythms as were older age and the presence of Alzheimer's disease. These findings support the hypothesis that 24-hour rhythms of DNA methylation, particularly near transcription start sites, may play a role in driving 24-hour rhythms of gene expression in the human dorsolateral prefrontal cortex, and may be affected by age and Alzheimer's disease.
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    Cross-tissue methylomic profiling strongly implicates a role for cortex-specific deregulation of ANK1 in Alzheimer’s disease neuropathology
    (2014) Lunnon, Katie; Smith, Rebecca; Hannon, Eilis; De Jager, Philip; Srivastava, Gyan; Volta, Manuela; Troakes, Claire; Al-Sarraj, Safa; Burrage, Joe; Macdonald, Ruby; Condliffe, Daniel; Harries, Lorna W.; Katsel, Pavel; Haroutunian, Vahram; Kaminsky, Zachary; Joachim, Catharine; Powell, John; Lovestone, Simon; Bennett, David A.; Schalkwyk, Leonard; Mill, Jonathan
    Alzheimer’s disease (AD) is a chronic neurodegenerative disorder characterized by progressive neuropathology and cognitive decline. We describe a cross-tissue analysis of methylomic variation in AD using samples from three independent human post-mortem brain cohorts. We identify a differentially methylated region in the ankyrin 1 (ANK1) gene that is associated with neuropathology in the entorhinal cortex, a primary site of AD manifestation. This region was confirmed as significantly hypermethylated in two other cortical regions (superior temporal gyrus and prefrontal cortex) but not in the cerebellum, a region largely protected from neurodegeneration in AD, nor whole blood obtained pre-mortem, from the same individuals. Neuropathology-associated ANK1 hypermethylation was subsequently confirmed in cortical samples from three independent brain cohorts. This study represents the first epigenome-wide association study (EWAS) of AD employing a sequential replication design across multiple tissues, and highlights the power of this approach for identifying methylomic variation associated with complex disease.