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In silico analysis to link insulin resistance, obesity,
and ageing with Alzheimer’s disease
Priyanka Sarkar
Vellore Institute of Technology: VIT University
Premkumar Jayaraj
Vellore Institute of Technology: VIT University
Ketaki Patwardhan
Vellore Institute of Technology: VIT University
Samiksha Yeole
Vellore Institute of Technology: VIT University
Sourajit Das
Vellore Institute of Technology: VIT University
Yash Somaiya
Vellore Institute of Technology: VIT University
Rajagopal Desikan
Vellore Institute of Technology: VIT University
Kavitha Thirumurugan ( m.kavitha@vit.ac.in )
Vellore Institute of Technology: VIT University https://orcid.org/0000-0002-4673-4099
Research Article
Keywords: Ageing, insulin resistance, Alzheimer's disease, Drosophila, TRKB signalling, phytocompounds,
neurological disorders, memory
Posted Date: June 10th, 2021
DOI: https://doi.org/10.21203/rs.3.rs-512487/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Read Full License
Version of Record: A version of this preprint was published at Journal of Molecular Neuroscience on July
5th, 2021. See the published version at https://doi.org/10.1007/s12031-021-01875-x.
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Abstract
The process of ageing accompanies several metabolic diseases. With ageing, fats accumulate to
increase the visceral and abdominal adiposity leading to hyperinsulinemia, insulin resistance, obesity and
several other diseases.
Drosophila melanogaster
is often used to study the ageing process and its related
disorders. Therefore in this study, we performed an
in silico
analysis to relate the process of ageing and
insulin resistance. We analyzed data of insulin resistant
drosophila
from GEO database and compared it
with the data from the literature survey. We observed that 98 genes were common in both the models, and
they showed gene modulations related to metabolic pathways, fatty acid metabolism, insulin resistance,
and neural receptor-ligand binding pathways. Analysis of the REACTOME database against human data
revealed that TRKB signalling pathway is commonly affected. TRKB mediated BDNF pathway is a major
regulator of memory loss. We further analyzed the common genes in Alzheimer's disease and compared
the y data with human data to identify the diseases related to these common genes. Then we performed
a literature survey to provide protective mechanisms for TRKB signalling pathway activation, mediated
through polyphenols. We treated the ies with sesamol conjugated lipoic acid derivative (a phenolic
compound) at hormetic doses to evaluate its effect on the memory of ies.
Introduction
Ageing is an irreversible process of multicellular organisms and unicellular organisms. Scientic
community is researching and adding hypotheses to elaborate on the cellular and molecular machinery
of ageing. Recent research in this eld has made it progressively clear that ageing is due to the build-up
of molecular damage, which gives a unied theory of ageing. Ageing is a process that predisposes
metabolic imbalances like insulin resistance and oxidative stress that ultimately lead to age-related
disorders like obesity, diabetes, neurological disorders, and memory impairments (de la Monte 2017). For
decades
drosophila
has been used as a model organism to study ageing and age-related diseases.
Drosophila melanogaster
belongs to the genus
drosophila
of family Drosophilidae. This
Drosophila
genus contains about 1,500 different species, and they have diversity in appearance, behaviour, and
breeding habitat.
D.melanogaster
has been widely used in genetic research and is a preferred model
organism in developmental biology studies (Deepa Parvathi V, Akshaya Amritha S 2009).
Drosophila
is
the dominant model used to understand the development of an organism from an embryo to an adult.
Many genes of
drosophila
are homologous to human genes and therefore studied to gain a better
understanding of these genes in humans (Jennings 2011). Pathways like malonate–acetate, shikimic
acid, and isoprenoid are involved in polyphenol production. They have proven therapeutic effects against
several pathological conditions, including neurodegenerative diseases (Stewart and Stewart 2008).
Sesamol mitigates memory impairment and causes neuroprotection via activation of Nrf2, NFκB and
BDNF (Kumar et al. 2010; Liu et al. 2017, 2018; Ren et al. 2018).
Therefore in this study, we have tried to identify the common genes involved in ageing, insulin resistance,
and neurodegenerative diseases. We have also analyzed the effect of a phenol derived synthetic
compound's ability to mitigate age-related memory impairment.
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Materials And Methods
Gene Expression data
We used the Gene Expression Omnibus (GEO) database to obtain
drosophila
insulin resistant obese
samples and ageing samples data. We have analyzed the data set (GSE105448) for high-sugar fed male
drosophila
against normal diet-fed male
drosophila
. These samples are insulin resistant and obese. We
obtained ageing y data from a literature survey on genetic responses towards mating and ageing in
drosophila
(Zhou et al. 2014). We also used the dataset (GSE48681) for analyzing the Alzheimer's
disease (AD) model ies. In this data we have utilized the 3-day old y data as young control ies and the
20-day old y data as aged diseased ies. The data up to 10% false discovery rate (FDR) only was used.
We have obtained the data from GEO database and literature to ensure their reliability. The data utilised
for the
in silico
work has been collected from previously published works and is analyzed through
published, and frequently used reliable end-user bioinformatics software.
Gene Ontology
Functional interpretation for each data set was performed individually through DAVID
(https://david.ncifcrf.gov/). It is a free online tool used for gene ontology studies (Dennis et al. 2003).
Drosophila melanogaster
was selected as the background, and all other parameters were kept in default
mode. Venn diagram was also generated to deduce the overlap between the two datasets using
InteractiVenn online tool. We explored the ageing data set and insulin resistant data set to nd the
common genes.
Comparison With Human Data
The data sets analyzed through REACTOME database within the human genome display TRKB mediated
signalling pathway. Specically, the pathways enhanced in age-related gene set show correlations to
TRKB signalling pathways mediated through BDNF, NTF3, and NTF4 (Supplementary data 2a, 2b). In
comparison, the high sugar-fed y data from gene enrichment analysis revealed the involvement of
GABA, NTF3, NTF4, TRKB and BDNF (Supplementary data 3). BDNF and other neurotropic factors NTF3
and NTF 4 are essential players of neural plasticity and survival. When the axons of the distal segment of
nerves degenerate due to damage in the peripheral nerves, the axons of the proximal segment start
budding; that gradually grow and eventually forms a connection with the target organ to restore its
function. In the absence of NTF, the proximal segment begins to degenerate rapidly, and the cell body
dies. BDNF mainly acts through TRKB pathway and plays a vital role in learning and memory. TRKB acts
as a receptor for the neurotropic ligand BDNF and NT4 (Firuzi et al. 2015). BDNF can also inhibit the
phosphorylation of the GABA receptor (Xiao and Le 2016; Porcher et al. 2018; Xiang et al. 2019).
Modulation in TRKB signalling, and its transactivation can lead to neuronal damages. Therefore, proper
TRKB signalling is required for learning and memory. This modulation is the cause of age-related
neurodegenerative diseases observed in humans and
drosophila.
Next, we analyzed data from
Alzheimer's disease (AD) to identify the common genes between insulin resistant/obese ies and AD ies.
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Fly Husbandry And Diet Preparation
Wild type
Drosophila melanogaster
ies (Canton-S) were reared at controlled temperature 25°C ± 1°C and
light:dark cycle (12:12 hours). Flies were maintained in 300 ml polypropylene bottles containing 30 ml of
maintenance diet (MM diet) (10% semolina (w/v), 10% jaggery (w/v), 1.5% agar (w/v), 3% methyl paraben
(v/v), and 0.3% propionic acid (v/v) (Chattopadhyay et al. 2015). Eggs were collected and transferred to a
new bottle. Newly emerging ies were segregated based on sex. Then, these ies were transferred to 2
different diets: (1) standard Sucrose-Yeast diet (SYD) (10% sucrose (w/v), 10% yeast extract (w/v), 2%
agar (w/v), 3% methyl paraben (v/v), and 0.3% propionic acid (v/v) (Chattopadhyay et al. 2015). (2) High
fat diet (HFD) (10% sucrose, 10% yeast extract, 2% palmitate, 2%Tween-80 and 1.5% agar, 3%
methylparaben and 0.3% propionic acid). For sesamol-conjugated lipoic acid-derivative supplementation,
the compound was dissolved in 0.5% DMSO and added into SYD and HFD at nal concentrations of 30
µM, and 60 µM by proper mixing. Standard control diets contained only water as a vehicle.
Memory Assay
Age matched
drosophila
ies were sorted into a group of 10 ies based on their sex for each set. An in-
house T-maze apparatus was built, and a modied protocol from JOVE was used for this assay (Malik
and Hodge 2014). All the experiments were conducted under dim red light to block the visual inputs for
the ies.We introduced the ies to a training tube attached to the T-maze. They were then allowed to
adapt to the tube and airow for 2 minutes.Then the rst odour (yeast) was introduced in one of the arms
of the T-maze with a 60-V shock (consisting of 1.25-sec pulses with 3.75-sec interpulse intervals) for a
total duration of 1 minute. We calculated the time with a stopwatch. While doing this, we attached only
one arm and removed the other arm. We followed the same way while introducing the second odour. The
ies were given a 30 sec rest period and then introduced to the second odour (banana) for 60 sec without
any shock. Then again, we gave a rest period of 30 sec, and the ies were nally moved from the training
chamber into the central chamber of the T-maze for 90 sec. Then both the tubes were tted into the
bottom of the apparatus to form the T-maze.
Short Term Memory Retention
The ies were simultaneously exposed to both the odours and were allowed to move towards them. The
test was conducted for 120 sec to allow maximum (80%) mobility. The memory retention analysis was
recorded for 3 times with a gap of 10 minutes and the average was utilized as the nal result. We
recorded the ies that avoided the punishing chamber odour against the total number of ies as the
percentage of ies retaining short term memory.
Long Term Memory Retention
We trained batches of ies in 2 cycles of spaced training with a 6-hour inter-cycle interval. Then long term
memory was evaluated, 12-hour after the training. Six-hour interval was considered because one-cycle
training in
drosophila
leads to the formation of a labile-phase of memory detected for up to 7 hrs.
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Results And Discussion
Gene and genome analysis
Drosophila
has served as a model organism for many human diseases and disorders due to its homology
with
Homo sapiens.
We have analyzed the GEO database and published literature to obtain data for
genomic comparison between ageing ies and insulin resistant obese ies. Insulin resistance led by
inammation is the root cause of many metabolic diseases. Recently, insulin resistance has been marked
as a characteristic feature of the normal ageing process. Normal ageing is accompanied by fat
deposition and lipid accumulation in the abdomen and visceral compartments leading to age enhanced
insulin resistance or hyperinsulinemia (Ryan 2000; Refaie et al. 2006). The data obtained from the
literature survey and GEO database revealed 482 genes that are differentially expressed during the
process of aging and also insulin resistance during obesity lead to the modulation of 1267 genes. The
data sets were analysed for their gene ontologies (Supplementary data 1). We observed that the top
ranked biological process affected by the aging process were cytoskeleton and synapse organisation,
immune responses and metabolic processes. The gene ontology analysis of obese/insulin resistant
sample data revealed the modulation of receptor signals and signal transduction, synaptic transmissions
and organization, cytoskeleton organisation and circadian rhythm entrapment. Most of the metabolic
pathways, hippo signalling pathways, fatty acid biosynthesis-related pathways, cytokine-mediated
pathways, and neural receptor-ligand interacting pathways were regulated by the listed gene sets. We
observed that the genes listed in ageing data and the gene list of insulin resistant obese data had a few
similarities based on their gene ontology. These similarities between these two data sets provoked us to
investigate the common genes between these two datasets. Among the reported genes, 98 genes were
common (Table1) in both aging as well as insulin resistant conditions (Fig.2).
Further a comparison between the y model and human in general was performed. The similarities within
pathways were obtained by comparing the
Drosophila
genome with the human genome using
REACTOME database (https://reactome.org/) (Fig.1).
The Relation Between Insulin Resistance/obesity And Ad
The comparison between the data sets of AD and the insulin resistant/ obese model revealed that there is
a signicant number of genes that commonly regulate both the diseases (Supplementary data 4). The
functional annotation and the analysis of enrichment clusters for the standard gene sets revealed their
involvement in the stimulus, metabolic, biosynthesis, and synapse related biological processes
(Supplementary data 4, Fig.3). The biological functions related to these common genes majorly included
synaptic communication, reexes towards the light, sound, mechanistic, and, abiotic stimulus (Table2).
When these common genes were analyzed against human data, many neurological diseases were
predicted for this dataset (Fig.4). There are genes that can commonly regulate and affect the occurrence
/ maintenance of both the diseases and might be associated with the ageing process also. Thus, we next
attempted to search the literature for phytocompounds that might retard the ageing process and the
