ACTA UNIVERSITATIS
UPSALIENSIS UPPSALA
2021
Digital Comprehensive Summaries of Uppsala Dissertations
from the Faculty of Medicine
1739
The role of HMG-coenzyme A
reductase (HMGCR) and statin
medication in the Central Nervous
System
Cognitive Functions, Metabolism, Feeding and Sleep
Behaviour
AHMED ALSEHLI
ISSN 1651-6206 ISBN 978-91-513-1177-7 urn:nbn:se:uu:diva-439049
Dissertation presented at Uppsala University to be publicly examined in A2:208b, BMC, Husargatan 3, Uppsala, Thursday, 20 May 2021 at 16:14 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in English. Faculty examiner: Professor Heinrich Dircksen (Zoology Department, Stockholm University).
Abstract
Alsehli, A. 2021. The role of HMG-coenzyme A reductase (HMGCR) and statin medication in the Central Nervous System. Cognitive Functions, Metabolism, Feeding and Sleep Behaviour. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of
Medicine 1739. 35 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-1177-7.
Millions of people are currently on statin medications (HMGCR inhibitors) to prevent cardiovascular diseases. Despite considerable central nervous system expression, little is known about HMGCR function in the brain. In Paper I, we used Drosophila and rodent models and found that inhibiting Hmgcr expression in the insulin-producing cells of the Drosophila hypothalamus equivalent, known as the pars intercerebralis (PI), throughout development, significantly reduces the expression of Insulin–like peptides 2 and 3 (ILP2 and ILP3), severely decreasing insulin signalling. This reduction causes decreased body size, hyperglycemia, increased lipid storage, and hyperphagia. We also discovered that Farnesyl pyrophosphate synthase (Fpps), an enzyme downstream of Hmgcr in the mevalonate pathway, is required for ILP2 expression in the PI. In rodents, acute inhibition of hypothalamic Hmgcr stimulates food intake as well. Furthermore, in rats, we found two regions within the hypothalamus that had significantly increased neural activity, the paraventricular nucleus and arcuate nucleus, which are known to regulate food intake. In Paper II, we explored the effects of statins on cognition and performed an observational study on a population-based sample from the UK Biobank. Cognitive performance in terms of reaction time, working memory and fluid intelligence was analysed at baseline and two follow-ups. Subjects were classified depending on age (up to 65 and over 65 years). The effect of statin use differed between the two age groups, with a beneficial effect on reaction time in older persons and fluid intelligence in both age groups, and a negative effect on working memory in younger subjects. In Paper III, we examined association of single nucleotide polymorphisms within the HMGCR gene, rs17238484 and rs12916, with self-reported insomnia symptoms. We found that statin users are associated with a higher risk for self-reported insomnia. The HMGCR genetic variants were also associated with self-reported insomnia, but in different manner. Carriers the rs12916-T risk allele had a protective effect from insomnia symptoms. No associations were found for either statin takers or carriers of these HGCMR risk alleles and late evening chronotype. The increased risk of insomnia noted with statins is partially explained by a mechanism that might be independent of HMGCR inhibition. In Paper IV, we discovered a novel role for Hmgcr in sleep regulation in Drosophila, where lacking of pan-neuronal Hmgcr expression causes sleep-promoting effects. We also found that loss of Hmgcr expression specifically in the PI insulin-producing cells, recapitulates the effect of pan-neuronal Hmgcr inhibition. Conversely, inhibiting Hmgcr in only six PI DH44 expressing neurons has the opposite effect on sleep, increasing sleep latency and decreasing sleep duration. This bi-functional property of Hmgcr in the fly brain underlies its importance in sleep regulation. Furthermore, loss of Hmgcr showed no effect on circadian rhythm, suggesting that Hmgcr regulates sleep by pathways distinct from the circadian clock.
Keywords: Statin, cardiovascular disease, HMGCR, PCSK9, sleep, insomnia, circadian,
Chronotype, feeding
Ahmed Alsehli, Department of Neuroscience, Schiöth: Functional Pharmacology, Box 593, Uppsala University, SE-751 24 Uppsala, Sweden.
© Ahmed Alsehli 2021 ISSN 1651-6206 ISBN 978-91-513-1177-7
List of Papers
This thesis is based on the following papers, which are referred to in the text by their Roman numerals.
I. Michael J. Williams, Ahmed M. Alsehli, Sarah N. Gartner, Si-fang Liao, Laura E. Clemensson, Anders Eriksson, Kiriana Is-grove, Lina Thelander, Maryom Nikpour, Zaid Khan, Pavel M. Itskov, Thiago C. Moulin, Valerie Ambrosi, Mohamed H. Al-Sa-bri, Martina Blunder, Pawel K. Olszewski and Helgi B. Schiöth. The statin target Hmgcr regulates energy metabolism and food intake through central mechanisms in Drosophila. (Submitted) II. Ahmed M. Alsehli, Gaia Olivo, Laura E. Clemensson, Michael
J. Williams and Helgi B. Schiöth. The Cognitive Effects of Statins Are Modified by Age. Sci Rep 10, 6187 (2020).
https://doi.org/10.1038/s41598-020-63035-2.
III. Ahmed M. Alsehli, Laura E. Clemensson, Gull Rukh,
Diana-Maria Ciuculete, Xiao Tan, Mohamed H. Al-Sabri, Michael J. Williams, Christian Benedict and Helgi B. Schiöth. Differential associations of statin treatment and polymorphism in genes cod-ing for HMGCR and PCSK9 to risk for insomnia. (Manuscript)
IV. Ahmed M. Alsehli, Sifang Liao, Mohamed H. Al-Sabri, Lukas
Vasionis, Archana Purohit, Neha Behare1, Laura E. Clemensson, Michael J. Williams and Helgi B. Schiöth. HMG-coenzyme A reductase (Hmgcr) regulates consolidation and homeostasis of sleep in Drosophila. (Manuscript)
Contents
Introduction ... 11
1- Statin therapy and its benefits ... 11
2- Mode of action of statin ... 11
3- Statin toxicity ... 12
3- Statin and HMGCR gene expression in the brain ... 13
Aims ... 15
Materials and Methods ... 16
Drosophila Studies ... 16
Fly maintenance ... 16
Fly strains ... 16
Macronutrient diets ... 16
RNA extraction, cDNA synthesis and quantitative real-time PCR (qPCR) ... 16
Capillary feeding (CAFE) assay ... 17
Western blot ... 17
Stress assay ... 18
Locomotor activity assay ... 18
Statistical analysis ... 18
Human studies ... 20
Subjects and data ... 20
Statins ... 20 Cognitive assessment ... 20 Single-nucleotide polymorphisms ... 21 Insomnia ... 21 Chronotype ... 21 Statistical analysis ... 22
The effect of statin use and age on cognitive function ... 22
Association between statins and polymorphism for genes coding HMGCR and PCSK9 to risk for insomnia and chronotype ... 22
Results ... 23
Paper I ... 23
Paper II ... 24
Paper IV ... 26
Discussions and conclusions ... 27
Acknowledgment ... 31
Abbreviations
HMGR 3-hydroxy-3-methylglutaryl-coenzyme A reductase
PCSK9 proprotein convertase subtilisin/kexin type 9
CVD cardiovascular disease
ACC / AHA American College of Cardiology and American Heart Association
LDL-C low-density lipoprotein cholesterol
FPP farnesyl diphosphate
FPPS farnesyl diphosphate synthase
GGPP geranylgeranyl diphosphate
GGPPS geranylgeranyl diphosphate synthase FTase farnesyltransferase
GGTase geranylgeranyl transferase
mvk mevalonate kinase
mvd CAAX
mevalonate PP decarboxylase
C, cysteine; A, aliphatic amino acid; X, any amino acid
SNPs Single-nucleotide polymorphisms
CAFE capillary feeding assay
DAMS Drosophila activity monitoring system
11
Introduction
1- Statin therapy and its benefits
Statins (Hmgcr inhibitors) are the first-choice agent to prevent hypercholes-terolemia and effective for reducing the risk of cardiovascular disease (CVD)1, the main global cause of morbidity and mortality according to the World Health Organization. Statins are among the most prescribed drugs worldwide with an estimated 25% of adults > 65 years currently being under statin treat-ment, with these numbers predicted to increase in future2. For instance, in the US, one out of every four Americans older than 40 years old is on statin ther-apy to cut down the risk of atherosclerotic diseases3. Recently, the American College of Cardiology and American Heart Association (ACC /AHA) changed its guidelines for the management of hyperlipidaemia to enlarge the number of adults eligible for the initiation of statin therapy, from 37.5% to 48.6%, to include those without cardiovascular diseases4. Furthermore, statins are effective in lowering LDL-C (low-density lipoprotein cholesterol), and the meta-analysis study has reported that 22% of the relative risk of CVDs de-creased with each one mmol/L drop of LDL-C5.
2- Mode of action of statin
3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) is an endo-plasmic reticulum enzyme and the rate-limiting step in the mevalonate-cho-lesterol biosynthesis pathway (Figure 1)6,7. The mevalonate pathway is a cor-nerstone for cholesterol/isoprenoid biosynthesis and vital for cellular pro-cesses, and the statin target HMGCR is the gate step for this pathway7,8. The HMGCR is one of the most highly regulated enzymes; it catalyzes the Hmg-CoA which is formed by the Acetyl Hmg-CoA to mevalonic acid7. Then, mevalo-nate goes through several steps until reaching the prenylation of proteins. The second critical step in the mevalonate/isoprenoid pathway is the production of the farnesyl diphosphate (FPP), which is the mevalonate pathway’s direct product. At this step, the FPP can be converted to either: (1) the squalene then cyclized to produce lipid, this step is very sensitive to FPP levels, or (2) to the geranylgeranyl diphosphate (GGPP)9. The prenylation of protein requires two cytosolic enzymes, farnesyltransferase (FTase) and geranylgeranyl transferase (GGTase) 7. The prenylated protein is occurred by adding the 15 carbon of the
12
(farnesyl) or a 20 carbon (geranylgeranyl) isoprenoid to cys residue of protein-containing CAAX motif 10. Statins also have been shown to exert effects on these isopreniods9,11,12 because recently found that statin-induced non-lipid (pleiotropic) effects such as anti-inflammatory and antioxidant effects, cell proliferation and improved endothelial functions7,12,13.
Statin drugs mainly inhibit HMGCR enzyme activity, which leads to a re-duction of cholesterol synthesis in the liver. This rere-duction leads to increased LDL-C receptor expression at the surface of the liver cells, resulting in in-creased uptake of LDL from the blood and ultimately dein-creased plasma con-centrations of LDL-C by 20 to 55% and reducing other apolipoprotein B-con-taining lipoproteins3,14.
3- Statin toxicity
Despite the positive effects of statins in lowering cholesterol, morbidity and mortality of CVDs, non-adherence or discontinuation of statin medication is still a major dilemma in statin use. Furthermore, it has been reported an in-creased risk of readmission, myocardial infarction and CVDs death when statin therapy is discontinued15. This emerges from several side effects of statin therapy, such as myopathy16, new-onset of type 2 diabetes17, neurocog-nitive effects and other complications18. Besides, the underlying mechanisms for these side effects are still unclear and lack consensus until now. In a clini-cal trial study is known as JUPITER, adults (n=17802) without diabetes at baseline were allocated into statin or placebo groups with follow-up for about five years17. In this study, statin-treated patients developed diabetes at a sig-nificantly higher rate compared to the placebo group. Furthermore, a large meta˗analysis of two HMGCR single nucleotide polymorphisms (SNPs), in-cluding 43 studies with 223,463 individuals, and randomized controlled trials of statin treatment in 129,170 participants, concluded that the HMGCR SNPs and statin treatment were similarly associated with lowering LDL-C concen-tration while raising the risk for type 2 diabetes and bodyweight gain19. Re-cently, HMGCR has been linked to human obesity by genome-wide associa-tion studies of body mass index (BMI)20. Moreover, several case reports and studies indicated that statin might cause cognitive impairment such as memory loss. However, this statement is still under considerable debate as statins might work as potential agents for managing Alzheimer’s diseases18. Furthermore, several lines of evidence found that statins might have neuropsychiatric ef-fects, such as aggression, mode changes and sleep disturbances, including in-somnia21,22.
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3- Statin and HMGCR gene expression in the brain
Cholesterol in the CNS constitutes about 25% of the whole lipid in the body23. Generally, lipid homeostasis is regulated by HMGCR enzyme. In the CNS, it has been shown that statin drugs can alter the net cholesterol level through inhibition of the HMGCR enzyme24,25. Although all statin drugs have the same mode of action, they are classified into two major categories: lipophilic, such as atorvastatin, lovastatin, and simvastatin, and hydrophilic, such as pravas-tatin, rosuvaspravas-tatin, and fluvastatin26. Nonetheless, both classes are detected in the brain. They have been shown to modify multiple genes’ expression, in-cluding those known to regulate metabolism (IGFBP3 and GPI) and feeding behaviour (NPY1R and CACNA1G)27. It is important to note that the meva-lonate pathway is conserved in all species. Also, statin drug has been shown to work in the mevalonate pathway of the Drosophila melanogaster10,28. Fur-thermore, HMGCR is distributed in the brain, such as the cerebral cortex, hip-pocampal formation and hypothalamus10,29,30.
14
Figure 1: Schematic diagram for the mevalonate pathway of human and
Dro-sophila conserved gene. The mevalonate pathway is highly conserved in
Drosoph-ila10. The statin target Hmgcr is an endoplasmic reticulum (ER) enzyme. The
farne-syl diphosphate (FPP) and geranylgeranyl diphosphate (GGPP) is directly can be in-hibited by HMGCR. The bifurcation step is the FPP which can be converted to ei-ther squalene to produce cholesterol by squalene synthase or to GGPP by GGPP synthase (GGPPS). The farnesyltransferase (FTase) and protein geranylgeranyltrans-ferase (GGTase) require for prenylation processes. 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA), mevalonate kinase (mvk), mevalonate PP decarboxylase (mvd), Gera-nyl diphosphate (GPP)31.
15
Aims
The aim of this thesis was to have a better understanding about the effects of statin therapy on the central nervous system. Furthermore, we wanted to pro-vide mechanistic insights into whether statin effects can be from the same mechanism as lowering cholesterol, in other words inhibition of the statin tar-get the HMGCR, or through pleiotropic statin effects. We also wanted to pro-vide a premise for future studies; and recommendations for statin users and clinicians for carefully monitoring during statin therapy. The aims of each pa-per are listed below.
Paper I
The aim of the Paper I was to investigate how Hmgcr linked to BMI by using different model systems, including fruit fly and rodents, and to identify a func-tion for Hmgcr in the brain, as well as to elucidate how it relates to energy metabolism and feeding behaviour.
Paper II
In Paper II, the main aim was to study if the effect of statin therapy on cogni-tive functions is dependent on age, by analyzing data from a large European population
Paper III
The aim of Paper III was to investigate a relationship between statin treatment as well as the genetically proxy inhibition of HMGCR and PCSK9 genes and the risk for insomnia from a large European population.
Paper IV
The focus of Paper IV was to investigate the effects of statin therapy and the Hmgcr on the sleep parameters by using genetically modified fruit flies.
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Materials and Methods
Drosophila Studies
Fly maintenance
Flies were reared on standard lab medium sugar/corneal/agar Jazz-mix Dro-sophila food (Fisher Scientific, Sweden) and mixed with extract yeast (VWR, Sweden) at 25°C with 50% relative humidity in a 12:12 hour light: dark cycle.
Fly strains
The following strains were used: w1118, UAS-Hmgcr RNAi from the Vienna
Drosophila RNAi Centre (VDRC, Austria), UAS-Hmgcr RNAi 2, elav-GAL4,
Dilp2-GAL4, 48Y-Gal4, DH44-GAL4 and UAS-tobi RNAi are all from the
Bloomington Stock Centre (Indiana, USA). The UAS-tobi overexpression line (referred to as tobiOE) was a gift from Dr. Michael Pankratz. The
elav-GAL80, a repressor of GAL4, was also gifted from Dr.Yuh Nung Jan.
Macronutrient diets
The flies were fed with different diets that consisted of varying concentrations of sucrose or yeast extract (from VWR, Sweden) in 1% agarose. For low sugar diet, we used 10 g/dl sucrose and 10 g/dl protein. Other diets used were 2.5 g/dl sugar:2.5 g/dl protein, 40 g/dl sugar:40 g/dl protein, 40 g/dl sugar:10 g/dl protein, and 10 g/dl sugar:40 g/dl protein. Adult male flies were maintained on these diets for five days at 29oC, 50% humidity on a 12:12 hour light:dark cycle.
RNA extraction, cDNA synthesis and quantitative real-time PCR
(qPCR)
The RNA extraction was performed by the phenol cholorform methods32 from the tissue samples. Either 40 fly heads or 10 fly bodies were homogenized in PBS for RNA extraction. We used an equal amount of phenol:choloro-form:isoamyl alcohol solution was added to the homogenized flies and mixed. Next, the solution was centrifuged for 5 min at 12,000g at at 40C. Afterwards,
17 the aqueous phase which contained RNA was transferred to a new tube and a similar amount of cholorform was added, followed by centrifugation, same as the previous mentioned speed and time. The ethanol (70%) was used to wash the pellet, then let to dry. To remove any DNA contamination, the sample was treated with DNAse and subsequently at 65°C for 15 min. The pellet was re-solved in 50 µl DEPC-H2O and incubated for 5 min. Afterword, the RNA solution centrifuged and transferred to a new tube. We used a spectrophotom-eter (model ND-1000, Nanodrop) to measure total RNA concentration. Sub-sequently, the High-capacity RNA-to-cDNA Kit (Applied Biosystems, Swe-den) was used for cDNA synthesis, and performed according to the manufac-turer’s instructions.
For qPCR, the relative expression levels of the genes of interest and house-keeping genes were determined by qPCR. A total volume of 20 µl, included 20 mM Tris/HCl pH 9.0, 50 mM KCl, 4 mM MgCl2, 0.2 mM dNTP, DMSO (1:20) and SYBR Green (1:50000) for each react was used. We used template concentration 5 ng/µl and the concentration of each primer was 2 pmol/µl. The qPCR Amplifications were performed with 0.02 µg/ml Taq DNA polymerase (Biotools, Sweden), with initial denaturation at 95°C for 3 min, followed by 50 cycles of denaturing at 95°C for 15 s, annealing at 52.8–60.1°C for 15 s and extension at 72°C for 30 s. The relative expression was normalized to the housekeeping gene and calculated by the double delta Ct method. The statis-tical analysis was One-way ANOVA to detect the differences in the gene ex-pression between the groups. If the P-value was less than 0.05, it was consid-ered significant differences between the groups.
Capillary feeding (CAFE) assay
In this method, we used a vial 9 cm by 2 cm (height by diameter), containing 1% agarose (5 cm high) to provide moisture and humidity for the flies. A cal-ibrated capillary glass tube (5 µl, VWR International) was filled with liquid food which contains 5% sucrose, 5% yeast extract and 0.5% food-colouring dye. To prevent the liquid food from evaporating, a layer of mineral oil was used. Adult male flies (aged 5-7 days old), were put inside the chamber and the opening of the vial was covered with paraffin tape, with a capillary tube being inserted from the top through the tape. The experiment was run at 25°C with 50% humidity on a 12:12 hour light:dark cycle. 10 replicates were per-formed for each genotype.
Western blot
Flies were homogenized in RIBA buffer (including protease and phosphotase inhibitors), then we loaded equal amount of lysate into SDS-PAGE gel and
18
blotted to the PVDF membrane. The following antibodies were used, Phos-pho-Drosophila Akt (Ser505) Antibody at 1:1000 dilution (cell signalling #4054), Akt (pan) (C67E7) Rabbit mAb (cell signalling #4691) at 1:1000 di-lution and beta Actin polyclonal Antibody (ThermoFisher # PA5-16914) at 2-4 µg/ml dilution. By using mild stripping protocol from Abcam, the blots were stripped and reprobed in the same PVDF membrane, and the primary antibod-ies were used in the following order Phosph-Akt, Pan Akt and beta Actin. We used the secondary antibody linked with Horseradish Peroxidase (HRP) at 1:10,000 dilution. Enhanced reagent ECL kits from Biorad were used for de-tecting the signals. The data from western blot was quantified by using the image J software.
Stress assay
To test the paraquat resistance, 70-80 flies raised after eclosion in vials con-taining 5 ml of either high sugar or low sugar diets for 5 days. Then, we starved the flies by transferring them to empty vials for 6 hours to remove all the re-maining food that would be left into the gut. Next, flies were moved to vials having just filter paper which was soaked into 20mM of paraquat (sigma Ref. 36541) in 5% of sucrose solution, with changing the filter paper every 24 hours. The survival rate was recorded until flies died.
Locomotor activity assay
We employed the Drosophila Activity Monitor system (DAMS, Trikinetics) to test the circadian-sleep-activity program of Drosophila flies. Each fly (aged 3-5 days) was placed into plastic tubes containing food for 5-6 days at the 12:12 light: dark conditions. The DAMS system is provided with infrared beam light that is broken by flies to detect movements (Figure 2). We used a single processing toolbox (SCAMP) from the Trikinetics, which is imple-mented in MATLAB, to analysis the sleep-activity behaviour of the flies. For the circadian rhythms test, flies were entrained for 3 days at normal light: dark condition, then the light is switched off for 5-6 days in constant dark: dark condition. For GAL80 protein, flies were entrained for 3 days at 180C in 12:12 light: dark cycle to activate the GAL80, therefore, the expression of UAS transgene is inhibited. By raising the temperature to 290C, the GAL80 protein was inactivated. By transferring the temperature to 180C, the GAL80 protein is reactivated again. This strategy allows us to transiently inhibit the interested gene. Furthermore, sleep is defined as no movement for 5 minutes33,34.
Statistical analysis
The analyses were performed with Prism using ANOVAs analysis. The mean and standard error from all replicates of each experiment were calculated.
19
Figure 2. Schematic diagram strategy of recording the sleep/activity behaviour of the Drosophila flies. A, flies were loaded in the tubes, the DAMS has an infrared
beam light. Once fly crosses this beam light, it is detected by the DAMS and counted as a single move. (B), Activity is recorded during light and dark times.
20
Human studies
Subjects and data
We used the UK Biobank cohort study, which is a collection of longitudinal health-related data and biological samples from > 500,000 participants (http://www.ukbiobank.ac.uk/). All people were live in the United Kingdom. The first assessment (baseline) was conducted between 2006 and 2010. Around 20,000 participants were followed up on during 2012 and 2013 for the second assessment. For the third assessment, participants further recalled be-tween 2015 and 2016. Subsequently, we extracted data regarding the use of statins at all three assessments, included additional covariates as following: ethnic background, age, sex, qualification, sleep duration, BMI, alcohol intake frequency, physical activity, diabetes, heart attack, angina, neurological and psychiatric diseases, stroke, medication for antihypertensive, insulin therapy. People who reported a white ethnic background were only included to mini-mize the confounding effects. People with a history of psychiatric and/or neu-rological disorders as diagnosed according to the ICD-10 criteria were ex-cluded as well as individuals who reported to have been diagnosed with stroke. For genetic analysis, some participants were excluded due to either the effect of relatedness or quality-control failure of the samples genotyped with UK BiLEVE.
Statins
The information about statin therapy was collected by self-reported or hospital admission data. Also, the participants were asked whether they used statins regularly or not. The prescribed statin drugs included atorvastatin, rosuvas-tatin, pravasrosuvas-tatin, fluvasrosuvas-tatin, lovasrosuvas-tatin, simvasrosuvas-tatin, and pitavastatin.
Cognitive assessment
We assessed three different types of cognitive functions: reaction time, pairs matching, and fluid intelligence. The reaction time was based on 12 rounds of the card-game ‘Snap’, and the participants were shown two cards at a time. If both cards matched, participants were instructed to press a button-box as
21 quickly as possible. The average time to correctly identify matches was rec-orded and used as an outcome. For fluid intelligence, this test was based on measures of the capacity to solve problems that need logic and reasoning abil-ity, independent of acquired knowledge. The participant needed to answer as many questions as possible within two minutes, and the total score was rec-orded. The pairs matching task occurred by memorizing the place matching pairs of cards. After the cards were turned face down on the screen, the par-ticipant was asked to touch as many pairs as possible in the fewest attempts. There were two rounds in this test; the first and second rounds used three and six pairs of cards, respectively. The outcome measure was to count the number of incorrect matches in the second round.
Single-nucleotide polymorphisms
We studied two single-nucleotide polymorphisms (SNPs) in the HMGCR gene (rs17238484 and rs12916) and one in the PCSK9 gene (rs11591147). These SNPs are confirmed to be associated with reduced protein function and lowered cholesterol levels. We also confirmed that all SNPs were in Hardy-Weinberg equilibrium.
Insomnia
At the first assessment (baseline), the self-reported insomnia symptoms were used; a part of a touch-screen questionnaire. The participants had to answer the question “Do you have trouble falling asleep at night, or do you wake up in the middle of the night?” by choosing one of the three semi-quantitative options: 1) “never/rarely”, 2) “sometimes” or 3) “usually”. People who an-swered no or only occasional insomnia symptoms as a control versus persons who reported ‘’usually’’ as cases, based on a previous publication35.
Chronotype
Assignment of a chronotype was based on the questions “Do you consider yourself to be?” and the answers “definitely a ‘morning’ person”, “more a ‘morning’ than an ‘evening’ person”, “more an ‘evening’ than a ‘morning’ person” or “definitely an ‘evening’ person”.
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Statistical analysis
We used the IBM Statistical Package for Social Science software (SPSS) ver-sion 24 for the main statistical analyses.
The effect of statin use and age on cognitive function
Over all three assessments, a longitudinal analysis was used to investigate the effects of statins therapy on cognitive functions. The mixed-effect generalized linear models were performed to measure the cognitive performance changes over time in statin users versus controls and middle-aged (up to 65 years) and old (over 65 years) participants. The time factor was set as random and others as fixed factors. First, we tested if there was an effect of statins on cognitive performance, then we checked for the interaction of statins and time as well as statins, time and age. The P-value was less than 0.017 for multiple correc-tions (0.05/3 cognitive tests).
Association between statins and polymorphism for genes coding
HMGCR and PCSK9 to risk for insomnia and chronotype
The baseline data for self-reported insomnia, SNPs, statin treatment and co-variates from the UK Biobank was used. Any answers “I don’t know” and “Prefer not to answer” were recoded as missing. The genotypes were coded as 0, 1, and 2 and included in regression models as predictor (independent) vari-able. Insomnia was treated as a dichotomous trait, where 0 represents controls and 1 insomnia cases and tested via binary logistic regression. Chronotype was treated as categorial (1–4) as well as dichotomous with “definite morning person” set to control and “definite evening person” set to the case. The sig-nificance was further adjusted to account for multiple testing: 0.05/2 (param-eters) = 0.025.
We first examined if the genetic instruments were associated with lower plasma lipid levels and incidence of a heart attack in our study population19,36 by using univariate linear regression and logistic regression, respectively. Then, we compared the prevalence of insomnia and the chronotype in the whole study population and our sub-cohorts by using covariate-adjusted bi-nary and multinomial logistic regression models. Furthermore, we run the in-teraction analysis between statin treatment and the presence of one of the SNPs using logistic regression models adjusted for the covariates.
23
Results
Paper I
Central Hmgcr regulates insulin expression, signalling and food intake in Drosophila.
It has been shown that Hmgcr is expressed in the Drosophila CNS, especially the Pars intercerebralis (PI)29. To confirm this, we employed immunohisto-chemistry and verified that Hmgcr was expressed in the insulin producing cells (IPCs). Consistent with Hmgcr expression requiring insulin signalling, starving the flies for 24 hours reduced Hmgcr transcription to nearly undetect-able levels within the IPCs. Using quantitative RT-PCR (qPCR), we validated that starvation significantly reduced Hmgcr head expression. However, when we kept the flies on diets containing various concentrations of macronutrients there was no significant effect.
Next, we wanted to determine if insulin signalling requires Hmgcr activity within IPCs of the PI. Since insulin is known to control Drosophila body size during development37, we knocked down Hmgcr expression specifically within the IPCs by using the Dilp2-GAL4 > UAS-Hmgcr RNAi (from now on referred to as Hmgcr males) throughout development to determine if there was an effect on body size. Raising the flies at 25 0C was sufficient to produce flies that were significantly smaller than controls. Raising Hmgcr males at 18 0C, which significantly reduces GAL4 activity38, was sufficient to rescue the phe-notype.
We also found that insulin-like peptide (Ilp2, Ilp3, Ilp5) and glucagon-like (Adipokinetic hormone, Akh) gene expression in adult males were signifi-cantly increased in Hmgcr males fed a high-sugar diet. Wild-type males treated with the Hmgcr inhibitor fluvastatin for 24 hours on a high-sugar diet increased Akh transcript levels, while 5 days of fluvastatin treatment signifi-cantly induced the transcript levels of Ilp2, Ilp3 and Akh.
We performed western blot analysis to clarify if the loss of IPC Hmgcr has a direct effect on insulin signalling. It was found that phospho-AKT (pAKT), a key molecule in the insulin signalling pathway39, in flies fed a high-sugar diet, significantly reduced in Hmgcr males compared to the controls indicating a reduction in insulin signalling. It was reported that reduced insulin signalling
24
protects flies against the effects of reactive oxygen species (ROS)40. There-fore, we measured the resistance to paraquat, which increases cellular ROS levels, using flies maintained on the two different diets. Hmgcr males main-tained on a high-sugar diet survived on paraquat-containing food significantly longer than controls, while those maintained on a low-sugar diet were not sig-nificantly different from controls.
Many lines of evidence show that insulin signalling in Drosophila regulates feeding behaviour41,42; therefore, we assessed food intake in Hmgcr males. In-terestingly, Hmgcr males maintained on a high-sugar diet were hyperphagic, while Hmgcr males fed a low-sugar diet showed normal food consumption. In support of these results, systemic inhibition of Hmgcr, by feeding wild-type flies a high-sugar diet containing fluvastatin, also induced hyperphagia, while wild-type flies maintained on a low-sugar diet containing fluvastatin ate nor-mally. To rule out peripheral effects, we knocked down Hmgcr in the corpus allatum and showed there was no effect on food intake. The corpus allatum is a peripheral endocrine gland where the Hmgcr enzyme is highly active42 and shown to be regulated by insulin29.
Paper II
Effects of statin use and age on cognitive performance over time
The use of statin medication had a significant influence on the performance of all three cognitive tests; but, in a differential manner. Also, at follow-ups, it was noticed that the effect of statin was generally weaker or absent, probably because of the lower sample number and resulting in higher variation rather than due to a true effect change. The cognitive performance was significantly influenced by user age.
Reaction time
Statin use significantly affected reaction time, with statin users performing overall better than controls. We noticed that the positive effect was detectable at all three assessments, although a significant statin and time interaction ef-fect and following post hoc analysis suggested that the efef-fect lost strength with repeated assessment, possibly due to smaller sample size and thus higher var-iation at follow-up. Moreover, there were significant statin, time and age in-teraction effect, and the post hoc testing identified that the effect of statin among the age groups was not similar. Specifically, statin use had a positive effect on reaction time only in old statin users, while there was no effect on the middle-aged statin users.
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Working memory
Working memory function was differently responded to statin medication. Statin had a different effect on longitudinal working memory function. Over-all, statin use significantly impaired test performance. We found that there were significant statin and time interaction with less effect in the second and third assessments. The statistical significance was only detected at the first assessment. The influence of statin therapy varied between the two age groups; the negative effect on working memory performance only being pre-sent in middle-aged but not old persons.
Fluid intelligence
Statin users showed overall improved reasoning abilities compared to con-trols. The use of statin had a positive influence at all assessments, although being weaker at follow-up. Both middle-aged and old statin users benefited from statin therapy in this test., while the results even were stronger in the younger group, still leading to a significant statin*time*age effect.
Paper III
A relationship between statins and polymorphism for genes coding HMGCR and PCSK9 to risk for insomnia.
The prevalence of insomnia in our study population was 28.3% of the partici-pants (mean age 56 ± 7.99 years). This was higher in women (32.2%) com-pared to men (23.8%). Statin users reported insomnia symptoms more often when compared to controls. After validating our genetic instruments, we ana-lyzed the association of rs17238484, rs12916 and rs11591147 genotypes with insomnia symptoms. Interestingly, gene variants in HMGCR and PCSK9 were both associated with insomnia but in a differential manner. We observed that each additional rs17238484-G risk allele was associated with a 1.9% lower risk for insomnia, which remained a trend after correcting for multiple com-parisons (P=0.045). More strongly, rs12916-T lowered the odds for insomnia with statistical significance by 2.1% (P=0.009). In contrast, we observed that each additional risk allele of PCSK9 rs11591147-T was associated with 10% higher odds for insomnia (P=0.001). Regarding chronotype, we did not detect an association of either statin treatment or HMGCR gene variants with chro-notype. However, each additional copy of the PCSK9 rs11591147-T allele was associated with 14% greater odds for evening preference (P=0.007).
26
Paper IV
Hmgcr regulates sleep parameters in the Drosophila. Silencing Hmgcr within neurons promotes sleep
To address the role of Hmgcr in regulating sleep, we knocked down pan-neu-ral Hmgcr expression by using the elav-GAL4 driver43 in adult male flies. The
elav-GAL4>UAS Hmgcr RNAi flies had significantly increased siesta and
night-time sleep levels because of increased sleep-episode duration, a decrease in the number of sleep episodes, and shortened sleep latency. Furthermore, the locomotor activity while awake was unchanged, indicating that the sleep ef-fects were not due to hypoactivity. To address further the role of pan-neural Hmgcr, we used the tubGAL80ts transgene flies to restrict the activity
UAS-Hmgcr RNAi driven by elav-GAL4. Flies were reared at 18 oC to make sure the expression of UAS-Hmgcr RNAi was highly suppressed. Raising the tem-perature to 290C, GAL80 protein was inactivated, and the consolidated sleep significantly increased. When the GAL80 was reactivated by shifting the tem-perature back to 18oC, the increased sleep was immediately rescued. Interest-ingly, the activity while awake was unchanged.
Central Hmgcr activity in different PI subgroups has opposite functions in sleep regulation
As mentioned above, PI is equivalent to the mammalian hypothalamus and responsible for various physiological functions, including sleep44. To address the function of Hmgcr in the PI, we knocked down Hmgcr expression specif-ically in the IPCs within the PI using Dilp2-GAL4. Similar to pan-neural knockdown of Hmgcr, we found that in flies where Hmgcr was knocked down specifically in Dilp2 neurons had significantly increased night sleep duration and the architecture of the sleep parameters was also similar to pan-neural knockdown of Hmgcr during the night time. However, when we used the
DH44-GAL4 driver to knock down Hmgcr in only six cells within the PI45, the sleep duration decreased in the Hmgcr knockdown flies compared to the con-trols. Interestingly, Hmgcr had no effects on the circadian rhythms.
27
Discussions and conclusions
We found that central Hmgcr activity regulates insulin signalling, leading to hyperglycemia, increased lipid storage and hyperphagia. This regulation is de-pendent on carbohydrate consumption. The hyperphagia phenotype was reca-pitulated in rodents fed a normal diet, where inhibiting Hmgcr activity in the hypothalamus led to increased neuronal activity in regions known to regulate food intake. This study provides evidence of how central Hmgcr regulation of metabolism and food intake could influence BMI.
Furthermore, previous studies are also inconclusive if there is a potential as-sociation between statin use and cognitive abilities, and a consensus has not been reached regarding the potential usefulness of statins in the prevention of dementia or Alzheimer disease18. This discrepancy in the results of previous studies has been suggested to be due to limitations in the sample analyzed, in particular, a lack of data on younger statin users, which would enable to assess of the specific effect of age on statin cognitive effects46. Therefore, we per-formed an observational study based on a large set of population-based data. This allowed us to study a possible modulatory influence of subject age on statin-related cognitive effects. Here, we found that the effect of statins altered depending on user age in terms of quality, strength and appearance. In partic-ular, reaction time in older persons was improved as well as fluid intelligence in both age groups. However, the working memory declined in middle-aged users.
On the other hand, one of the frequent complaints in general practice is in-somnia, which is highly prevalent and approximately 30‒35% of the global population is affected47. Depending on the severity, insomnia can be a serious condition with a large impact on the quality of life. There are several predis-posing factors for insomnia, including genetic factors and the use of medica-tion, and insomnia symptoms experienced as side effects of drug treatment may significantly affect the probability of a patient adhering to treatment. In this regard, sleep disturbances, including symptoms of insomnia, have been linked to the treatment with cholesterol-lowering drugs and statins in particu-lar. In order to gain a less confounded insight into the possible relationship between cholesterol-lowering drugs and sleep disturbances, as well as provid-ing mechanistic insight, we used the effects of genetic variants of the target
28
genes of cholesterol-lowering therapies, HMGCR and PCSK9, on self-re-ported insomnia symptoms in a large European study cohort. We found that statin treatment, as well as lower PCSK9 activity, was associated with a greater risk for insomnia, while lower HMGCR activity was linked to a re-duced risk for insomnia. These results have several direct implications: First, they suggest that the negative effect of statin treatment is independent of the effect of HMGCR inhibition, and second that the positive effect of HMGCR inhibition is independent of the effect of a downstream reduction in circulating LDL-C. Third, the negative effect of statin treatment, as well as inhibition of PCSK9, might instead be related to the lower cholesterol levels. These find-ings are intriguing, as they offer a possible explanation for some of the con-troversial outcomes in the literature. Whether or not the effect of statins in a given study had a negative or no effect on sleep might have been dependent on the proportion of persons carrying one of the frequent HMGCR or PCSK9 SNPs.
To further understand statin-induced alteration in sleep parameters, we used the Drosophila model. Our study found that Hmgcr plays a major role in the regulation of sleep in Drosophila and is able to modulate sleep parameters, indicating neurons that regulate sleep need Hmgcr activity as part of the sleep circuit. Our findings show that inhibiting pan-neural Hmgcr causes sleep-pro-moting effects due to increased sleep episode duration, decreased number of sleep episodes, as well as shorten sleep latency. Moreover, our results show that Hmgcr is important in the maintenance of sleep because sleep latency and duration of sleep episodes were modulated by inhibiting Hmgcr. Many lines of evidence indicate that the PI is responsible for regulating metabolism, sleep and circadian rhythm44,48. Also, the PI is a heterogeneous region that can be found to have both sleep-promoting and arousal-promoting effects46. Interest-ingly, we found that the PI required Hmgcr for sleep regulation. Hmgcr is crucial for the sleep-wake cycle mediated by the PI, where Hmgcr is among the molecular machinery modulating the shape function of PI neurons in rela-tion to sleep. Inhibiting Hmgcr specifically in Dilp2 neurons induces a similar sleep pattern to pan-neural Hmgcr knockdown during the night. In contrast to global Hmgcr suppression, knocking down Hmgcr in only six DH44 PI neu-rons leads to increased sleep latency and decreased total sleep duration. These changes in sleep parameters due to silencing the Hmgcr, suggesting Hmgcr modulate the sleep homeostat directly but independent of the circadian rhythms pathway (Figure 3).
29
Figure 3: Schematic diagram for the role of the central Hmgcr in pars intercer-ebralis (PI)-hypothalamus like structure in the Drosophila. (A-C) Hmgcr is
in-volved in the regulation of feeding and sleep behaviour but has no effect on the cir-cadian rhythms.
30
Perspectives
Statins are widely used medication for primary and secondary prevention of CVDs events. However, there are several side effects associated with statin medications that cause statin discontinuation or non-adherence. Our compre-hensive studies in statin therapy and statin-target inhibition HMGCR shed light on the mechanism of these complex side effects. It would be beneficial to increase statin adherence and promote general health49. Indeed, high adher-ence to statin therapy is associated with a lower risk of CVDs50. Moreover, our analyses highlight the importance of understanding the statin effects to improve knowledge and shape guidelines for clinicians when prescribing statins and evaluating their side effects in patients.
Intriguingly, our results show a role of Hmgcr for the sleep/metabolism ho-meostasis, offering a foundation for future studies. We have employed the fruit fly model in this thesis, which supports to use of Drosophila
melano-gaster for further understanding the effects of statins at the molecular and
be-havioural level. Consequently, the fly model provides additional opportunity to speed up the research concerning statins, considering that clinical trials could take years to answer some critical question in this context. On this basis, we are currently investigating another side effect associated with statin ther-apy, statin-induced myopathy, by using the fly model. Finally, in our human study, we found that statins can modulate cognitive performance suggesting that further research are warranted to characterize the role of Hmgcr for cog-nitive functions.
31
Acknowledgment
First and foremost, I would like to express my deepest and greatest thank to my main supervisor Professor Helgi B. Schiöth and co-supervisor Dr.
Mi-chael J. Williams, for all your support and guidance during my PhD period.
I always grateful for your time, creating a learning environment, interesting discussion, developed my skills in every single aspect of the research such as writing, analysis, critical thinking…etc., particularly given me the courage and confidence for how to be an independent in the research. I have learned a lot from you!
Thank you to Sifang Liao, Mohamed H. Al-Sabri, Lukas Vasionis,
Archana Purohit, Neha Behare, Diana-Maria Ciuculete, Xiao Tan to your
contribution to my work plus supporting each other in a warm and friendly atmosphere.
I extend my gratitude to Gaia Olivo, Laura E. Clemensson and Gull Rukh for their contribution to my studies and help me in handling data and the sta-tistical analysis. A special thanks to Christian Benedict for his positive con-tribution, discussion and sharing knowledge with me.
Thanks to all the wonderful colleagues in the Helgi’s Lab that I have met throughout the four years of my PhD: Misty Attwood, Hao Cao, Kimia
Hos-seini, Mehwish Akram, Sourabh Patil, Lieve van Egmond, Thiago Mou-lin, Jörgen Jonsson, Maud Miguet, Wen Liu and Eirini Kotsidou.
My deepest grateful to my loved family during whole my career, and thank you to all love, support and encouragement at all the time, especially my be-loved wife’’ Eman’’ and daughter ‘’Farah’’.
32
References
1. Yebyo HG, Aschmann HE, Kaufmann M, Puhan MA. Comparative effectiveness and safety of statins as a class and of specific statins for primary prevention of cardiovascular disease: A systematic review, meta-analysis, and network meta-analysis of randomized trials with 94,283 participants. Am
Heart J. 2019;210:18-28. doi:10.1016/j.ahj.2018.12.007
2. Wallach-Kildemoes H, Stovring H, Holme Hansen E, Howse K, Pétursson H. Statin prescribing according to gender, age and indication: What about the benefit-risk balance? J Eval Clin Pract. 2016;22(2):235-246. doi:10.1111/ jep.12462
3. Newman CB, Preiss D, Tobert JA, et al. Statin Safety and Associated Adverse Events A Scientific Statement from the American Heart Association. Arterioscler
Thromb Vasc Biol. 2019;39(2):E38-E81. doi:10.1161/ATV.0000000000000073
4. Pencina MJ, Navar-Boggan AM, D’Agostino RB, et al. Application of New Cholesterol Guidelines to a Population-Based Sample. N Engl J Med. 2014;370(15):1422-1431. doi:10.1056/nejmoa1315665
5. Silverman MG, Ference BA, Im K, et al. Association between lowering LDL-C and cardiovascular risk reduction among different therapeutic interventions: A systematic review and meta-analysis. JAMA - J Am Med Assoc. 2016;316(12): 1289-1297. doi:10.1001/jama.2016.13985
6. Zhong S, Li L, Liang N, et al. Acetaldehyde Dehydrogenase 2 regulates HMG-CoA reductase stability and cholesterol synthesis in the liver. Redox
Biol. 2021;41:101919. doi:10.1016/j.redox.2021.101919
7. Buhaescu I, Izzedine H. Mevalonate pathway: A review of clinical and therapeutical implications. Clin Biochem. 2007;40(9-10):575-584. doi:10.1016/ j.clinbiochem.2007.03.016
8. Goldstein JL, Brown MS. Regulation of the Mevalonate Pathway.; 1990. 9. Bonetti P. Statin effects beyond lipid lowering—are they clinically relevant?
Eur Heart J. 2003;24(3):225-248. doi:10.1016/S0195-668X(02)00419-0
10. Yi P, Han Z, Li X, Olson EH. The mevalonate pathway controls heart formation in Drosophila by isoprenylation of Gγ1. Science (80- ). 2006;313(5791):1301-1303. doi:10.1126/science.1127704
11. Lee M-H, Cho YS, Han Y-M. Simvastatin Suppresses Self-Renewal of Mouse Embryonic Stem Cells by Inhibiting RhoA Geranylgeranylation. Stem Cells. 2007;25(7):1654-1663. doi:10.1634/stemcells.2006-0753
12. Porter KE, Turner NA, O’Regan DJ, Balmforth AJ, Ball SG. Simvastatin reduces human atrial myofibroblast proliferation independently of cholesterol lowering via inhibition of RhoA. Cardiovasc Res. 2004;61(4):745-755. doi:10.1016/j.cardiores.2003.11.032
33
13. Sorrentino G, Ruggeri N, Specchia V, et al. Metabolic control of YAP and TAZ by the mevalonate pathway. Nat Cell Biol. 2014;16(4):357-366. doi:10.1038/ncb2936
14. Istvan ES, Deisenhofer J. Structural mechanism for statin inhibition of HMG-CoA reductase. Science (80- ). 2001;292(5519):1160-1164. doi:10.1126/s cience.1059344
15. Rodriguez F, Maron DJ, Knowles JW, Virani SS, Lin S, Heidenreich PA. Association of Statin Adherence with Mortality in Patients with Atherosclerotic Cardiovascular Disease. JAMA Cardiol. 2019;4(3):206-213. doi:10.1001/jamacardio.2018.4936
16. Keen HI, Krishnarajah J, Bates TR, Watts GF. Statin myopathy: The fly in the ointment for the prevention of cardiovascular disease in the 21st century? Expert
Opin Drug Saf. 2014;13(9):1227-1239. doi:10.1517/14740338.2014.937422
17. Ridker PM, Danielson E, Fonseca FAH, et al. Rosuvastatin to Prevent Vascular Events in Men and Women with Elevated C-Reactive Protein. N
Engl J Med. 2008;359(21):2195-2207. doi:10.1056/NEJMoa0807646
18. Schultz BG, Patten DK, Berlau DJ. The role of statins in both cognitive impairment and protection against dementia: A tale of two mechanisms.
Transl Neurodegener. 2018;7(1). doi:10.1186/s40035-018-0110-3
19. Swerdlow DI, Preiss D, Kuchenbaecker KB, et al. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: Evidence from genetic analysis and randomized trials. Lancet. 2015;385(9965):351-361. doi:10.1016/S0140-6736(14)61183-1
20. Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197-206. doi:10.1038/nature14177
21. Broncel M, Gorzelak-Pabis P, Sahebkar A, et al. Sleep changes following statin therapy: A systematic review and meta-analysis of randomized placebo-controlled polysomnographic trials. Arch Med Sci. 2015;11(5):915-926. doi:10.5114/aoms.2015.54841
22. MHRA PUBLIC ASSESSMENT REPORT Statins: Updates to Product Safety Information.; 2009.
23. Segatto M, Di Giovanni A, Marino M, Pallottini V. Analysis of the protein network of cholesterol homeostasis in different brain regions: An age and sex dependent perspective. J Cell Physiol. 2013;228(7):1561-1567. doi:10.1002/ jcp.24315
24. Gamba P, Testa G, Gargiulo S, Staurenghi E, Poli G, Leonarduzzi G. Oxidized cholesterol as the driving force behind the development of Alzheimer’s disease. Front Aging Neurosci. 2015;7(JUN). doi:10.3389/ fnagi.2015.00119
25. Hale RW, Dietschy JM. Is there a connection between the concentration of cholesterol circulating in plasma and the rate of neuritic plaque formation in Alzheimer disease? Arch Neurol. 2000;57(10):1410-1412. doi:10.1001/ archneur.57.10.1410
26. Schachter M. Chemical, pharmacokinetic and pharmacodynamic properties of statins: An update. Fundam Clin Pharmacol. 2005;19(1):117-125. doi:10.1111/j.1472-8206.2004.00299.x
34
27. Johnson-Anuna LN, Eckert GP, Keller JH, et al. Chronic administration of statins alters multiple gene expression patterns in mouse cerebral cortex. J
Pharmacol Exp Ther. 2005;312(2):786-793. doi:10.1124/jpet.104.075028
28. Levine BD, Cagan RL. Drosophila Lung Cancer Models Identify Trametinib plus Statin as Candidate Therapeutic. Cell Rep. 2016;14(6):1477-1487. doi:10.1016/j.celrep.2015.12.105
29. Belgacem YH, Martin JR. Hmgcr in the corpus allatum controls sexual dimorphism of locomotor activity and body size via the insulin pathway in Drosophila. PLoS One. 2007;2(1). doi:10.1371/journal.pone.0000187 30. Santos AC, Lehmann R. Isoprenoids control germ cell migration downstream
of HMGCoA reductase. Dev Cell. 2004;6(2):283-293. doi:10.1016/S1534-5807(04)00023-1
31. Wang M, Casey PJ. Protein prenylation: Unique fats make their mark on biology.
Nat Rev Mol Cell Biol. 2016;17(2):110-122. doi:10.1038/nrm.2015.11
32. CHOMZYNSKI P. Single-Step Method of RNA Isolation by Acid Guanidinium Thiocyanate–Phenol–Chloroform Extraction. Anal Biochem. 1987;162(1):156-159. doi:10.1006/abio.1987.9999
33. Hendricks JC, Finn SM, Panckeri KA, et al. Rest in Drosophila is a sleep-like state. Neuron. 2000;25(1):129-138. doi:10.1016/S0896-6273(00)80877-6 34. Tononi G. Correlates of sleep and waking in Drosophila melanogaster. Science
(80- ). 2000;287(5459):1834-1837. doi:10.1126/science.287.5459.1834
35. Jansen PR, Watanabe K, Stringer S, et al. Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. Nat
Genet. 2019;51(3):394-403. doi:10.1038/s41588-018-0333-3
36. Nelson CP, Lai FY, Nath M, et al. Genetic Assessment of Potential Long-Term On-Target Side Effects of PCSK9 (Proprotein Convertase Subtilisin/Kexin Type 9) Inhibitors. Circ Genomic Precis Med. 2019;12(1):e002196. doi:10.1161/CIRCGEN.118.002196
37. Brogiolo W, Stocker H, Ikeya T, Rintelen F, Fernandez R, Hafen E. An evolutionarily conserved function of the drosophila insulin receptor and insulin-like peptides in growth control. Curr Biol. 2001;11(4):213-221. doi:10.1016/S0960-9822(01)00068-9
38. Duffy JB. GAL4 system in Drosophila: A fly geneticist’s Swiss army knife.
Genesis. 2002;34(1-2):1-15. doi:10.1002/gene.10150
39. Brozinick JT, Birnbaum MJ. Insulin, but not contraction, activates Akt/PKB in isolated rat skeletal muscle. J Biol Chem. 1998;273(24):14679-14682. doi:10.1074/jbc.273.24.14679
40. Bonilla E, Medina-Leendertz S, Villalobos V, Molero L, Bohórquez A. Paraquat-induced oxidative stress in Drosophila melanogaster: Effects of melatonin, glutathione, serotonin, minocycline, lipoic acid and ascorbic acid.
Neurochem Res. 2006;31(12):1425-1432. doi:10.1007/s11064-006-9194-8
41. Broughton SJ, Slack C, Alic N, et al. DILP-producing median neurosecretory cells in the Drosophila brain mediate the response of lifespan to nutrition.
Aging Cell. 2010;9(3):336-346. doi:10.1111/j.1474-9726.2010.00558.x
42. Loh K, Zhang L, Brandon A, et al. Insulin controls food intake and energy balance via NPY neurons. Mol Metab. 2017;6(6):574-584. doi:10.1016/ j.molmet.2017.03.013
35
43. Berger C, Renner S, Lüer K, Technau GM. The commonly used marker ELAV is transiently expressed in neuroblasts and glial cells in the Drosophila embryonic CNS. Dev Dyn. 2007;236(12):3562-3568. doi:10.1002/dvdy.21372
44. Crocker A, Shahidullah M, Levitan IB, Sehgal A. Identification of a Neural Circuit that Underlies the Effects of Octopamine on Sleep:Wake Behavior.
Neuron. 2010;65(5):670-681. doi:10.1016/j.neuron.2010.01.032
45. Cavanaugh DJ, Geratowski JD, Wooltorton JRA, et al. Identification of a circadian output circuit for rest: Activity rhythms in drosophila. Cell. 2014;157(3):689-701. doi:10.1016/j.cell.2014.02.024
46. Power MC, Weuve J, Sharrett AR, Blacker D, Gottesman RF. Statins, cognition, and dementia-systematic review and methodological commentary.
Nat Rev Neurol. 2015;11(4):220-229. doi:10.1038/nrneurol.2015.35
47. Morin CM, Drake CL, Harvey AG, et al. Insomnia disorder. Nat Rev Dis
Prim. 2015;1. doi:10.1038/nrdp.2015.26
48. Siegmund T, Korge G. Innervation of the ring gland of drosophila melanogaster. J Comp Neurol. 2001;431(4):481-491. doi:10.1002/1096-9861(20010319)431:4<481::AID-CNE1084>3.0.CO;2-7
49. Dormuth CR, Patrick AR, Shrank WH, et al. Statin adherence and risk of accidents a cautionary tale. Circulation. 2009;119(15):2051-2057. doi:10.1161/ CIRCULATIONAHA.108.824151
50. Hirsh BJ, Smilowitz NR, Rosenson RS, Fuster V, Sperling LS. Utilization of and Adherence to Guideline-Recommended Lipid-Lowering Therapy After Acute Coronary Syndrome: Opportunities for Improvement. J Am Coll
Acta Universitatis Upsaliensis
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1739
Editor: The Dean of the Faculty of Medicine
A doctoral dissertation from the Faculty of Medicine, Uppsala University, is usually a summary of a number of papers. A few copies of the complete dissertation are kept at major Swedish research libraries, while the summary alone is distributed internationally through the series Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine. (Prior to January, 2005, the series was published under the title “Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine”.)
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