Carbon Chemist

Tag: Neurodegeneration

[ad_2]

Source link

  • 2021: Anti-amyloid antibodies take a bumpy road to the clinic

    2021: Anti-amyloid antibodies take a bumpy road to the clinic

    [ad_1]

    Nature, Published online: 26 September 2024; doi:10.1038/d41586-024-02952-y

    The arrival of the first disease-modifying therapy for Alzheimer’s was significant, but it was not met with the joy that might have been expected.

    [ad_2]

    Source link

  • Cell-to-cell tunnels rescue neurons from degeneration

    Cell-to-cell tunnels rescue neurons from degeneration

    [ad_1]

    Nature, Published online: 11 September 2024; doi:10.1038/d41586-024-02862-z

    Tiny cellular tubes between neurons and brain cells called microglia serve as conduits for the export of toxic protein aggregates from neurons and the import of healthy organelles, keeping neurodegeneration at bay.

    [ad_2]

    Source link

  • What accelerates brain ageing? This AI ‘brain clock’ points to answers

    What accelerates brain ageing? This AI ‘brain clock’ points to answers

    [ad_1]

    fMRI scan of a healthy human brain at rest shown in red, yellow and blue colours on a black background

    A functional magnetic resonance imaging scan (artificially coloured) of a human brain. Researchers used data from such scans to measure an aspect of brain ageing.Credit: Mark and Mary Stevens Neuroimaging and Informatics Institute/Science Photo Library

    A newly devised ‘brain clock’ can determine whether a person’s brain is ageing faster than their chronological age would suggest1. Brains age faster in women, countries with more inequality and Latin American countries, the clock indicates.

    “The way your brain ages, it’s not just about years. It’s about where you live, what you do, your socioeconomic level, the level of pollution you have in your environment,” says Agustín Ibáñez, the study’s lead author and a neuroscientist at Adolfo Ibáñez University in Santiago. “Any country that wants to invest in the brain health of the people, they need to address structural inequalities.”

    The work is “truly impressive”, says neuroscientist Vladimir Hachinski at Western University in London, Canada, who was not involved in the study. It was published 26 August in Nature Medicine.

    Only connect

    The researchers looked at brain ageing by assessing a complex form of functional connectivity, a measure of the extent to which brain regions are interacting with one another. Functional connectivity generally declines with age.

    The authors drew on data from 15 countries: 7 (Mexico, Cuba, Colombia, Peru, Brazil, Chile and Argentina) that are in Latin America or the Caribbean and 8 (China, Japan, the United States, Italy, Greece, Turkey, the United Kingdom and Ireland) that are not. Of the 5,306 participants, some were healthy, some had Alzheimer’s disease or another form of dementia and some had mild cognitive impairment, a precursor to dementia.

    Five ways the brain can age: 50,000 scans reveal possible patterns of damage

    The researchers measured participants’ resting brain activity — that when they were doing nothing in particular — using either functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). The first technique measures blood flow in the brain, and the second measures brain-wave activity.

    The authors computed the functional connectivity of each person’s brain and input those data into two deep-learning models trained to predict brain age, one for fMRI data and one for EEG data. They could then calculate each person’s ‘brain-age gap’ — the difference between their chronological age and their brain age estimated from functional connectivity. Having a brain age gap of ten years, for example, would mean that your brain connectivity is roughly the same as that of someone ten years older than you.

    Unequal gaps

    The models showed that people with Alzheimer’s or another type of dementia had larger brain-age gaps than both those with mild cognitive impairment and healthy controls.

    Participants from Latin American or the Caribbean had larger brain-age gaps, on average, than did those from other regions. Latin America is one of the most unequal region in the world, says Ibáñez, and he thinks that this is why the brains of people from that region aged faster. Structural socioeconomic inequality, exposure to air pollution and health disparities were linked to larger brain-age gaps, especially in people from Latin America.

    Moreover, women living in countries with high gender inequality — particularly those in Latin America and the Caribbean — tended to have larger brain-age gaps than did men in those countries.

    Other clocks, other continents

    Simply quantifying brain ageing in a sample this geographically diverse is a phenomenal achievement, says Hachinski. He thinks the conclusion that brain-age gaps vary is solid, but he cautions that functional connectivity is only one way of measuring the health of the brain, and that someone could have a lot of brain connectivity while having, for example, poor mental health due to conditions such as depression or anxiety. Neuroscience is “not good at measuring gestalts”, he says.

    Blood tests could soon predict your risk of Alzheimer’s

    One possible source of inconsistency in the data is the range of fMRI machines and EEGs — spread across 15 nations — that supplied the brain scans. For example, lower-income nations might have had older equipment that generated lower-quality data than those from higher-income nations. But Ibáñez found no association between lower data quality and either a larger brain-age gap or higher structural inequality.

    Now, Ibáñez’s team is investigating whether brain-age gaps are linked to national income by comparing brain-age gaps in groups from Asian nations and the United States, and adding data from ‘epigenetic’ clocks that measure biological age by examining chemical modifications on DNA. Eventually, Ibáñez hopes that the data will contribute to personalized-medicine approaches that are grounded in the full biological diversity of people’s brains around the world.

    “We need to understand this diversity,” says Ibañez. “We cannot create a truly global science of dementia without addressing this.”

    [ad_2]

    Source link

  • Alzheimer’s drug with modest benefits wins backing of FDA advisers

    Alzheimer’s drug with modest benefits wins backing of FDA advisers

    [ad_1]

    A blue, purple, pink and yellow coloured combined PET and CT scan of a brain with Alzheimer's disease on a black background

    Superimposed scans show the brain of a person with Alzheimer’s disease. Credit: Zephyr/Science Photo Library

    A drug for Alzheimer’s disease has won unanimous approval from independent scientists advising the US Food and Drug Administration (FDA), bringing the treatment closer to use in the clinic.

    The drug, donanemab, would be the second on the US market that slows the cognitive decline caused by the disease. But donanemab’s effects are modest, it does not reverse symptoms and the FDA might limit who can take it.

    At a 10 June meeting at the FDA’s headquarters in Silver Spring, Maryland, all 11 members of an FDA independent scientific advisory committee voted that donanemab, made by Eli Lilly, based in Indianapolis, Indiana, is effective at treating Alzheimer’s, at least in people at early stages of the disease, and that its benefits outweigh its risks.

    The advisory meeting itself was a surprise to many observers, who had expected the FDA to quickly approve donanemab without convening an advisory committee. Instead the FDA delayed its decision until after a public meeting could be held because of questions about the drug’s efficacy in people with certain markers of Alzheimer’s disease. But in the end, “it was a very positive meeting,” says neurologist David Knopman of the Mayo Clinic in Rochester, Minnesota, who was not on the committee. “It would have been difficult for someone to object based on the standard of the data.”

    Amyloid attacker

    Donanemab is an antibody that attacks amyloid, a sticky protein that accumulates in the brains of people with Alzheimer’s. In data submitted to the FDA, Lilly reported that the 860 trial participants who received donanemab lost their cognitive abilities more slowly over the course of 18 months than those who received a placebo. The drug, however, did not reverse the disease. Research1,2 shows that donanemab slows symptoms roughly as well as rival drug lecanemab, which also attacks amyloid. It is made by bio-pharmaceutical companies Eisai in Tokyo and Biogen in Cambridge, Massachusetts.

    More Alzheimer’s drugs head for FDA review: what scientists are watching

    Unlike previous trials of monoclonal antibodies, Lilly only tested people whose brains contained both amyloid and another protein called tau that is associated with cognitive decline. Donanemab seemed more effective in people who had low to moderate tau levels at the start of the trial than in people who had high levels. But the FDA pointed out that the disease might have progressed more slowly in the lower-tau group than it in those with higher tau.

    At the meeting, advisory committee members were broadly supportive of the drug. Some noted, however, that Lilly has little evidence that it works in people with no to very little tau. But the committee decided against restricting the drug’s usage on the basis of tau levels, because screening for tau is complex and costly. A screening requirement would prevent an unacceptably high number of people from accessing the drug, the committee decided.

    The panel members also expressed some concerns about a condition called amyloid-related imaging abnormalities (ARIA) that can cause brain bleeding and seizures. ARIA, which can be fatal, is thought to occur when the antibodies weaken blood vessels in the brain. Lilly recorded more ARIA-related deaths among people who received the drug than in the placebo group. Lecanemab also has been linked to ARIA, but the increased risk seems to be much higher with donanemab3.

    Controversial therapies

    The approval is a bright spot for amyloid-targeting Alzheimer’s drugs after numerous controversies. The FDA approved the first such drug, Biogen and Eisai’s aducanumab, in 2021 over the objections of its advisory committee, leading three committee members to resign in protest. A US Congressional investigation found that that the FDA had improperly guided the manufacturers through the approval process. Many insurers were unconvinced by the drug’s efficacy, and most refused to cover it. Biogen stopped making the drug this year. And three people died from ARIA-related conditions during clinical trials of lecanumab.

    Landmark Alzheimer’s drug approval confounds research community

    The donanemab committee said that more research is still needed on the drug, including how long people should take it, and its efficacy in people with different levels of tau. Knopman says that it remains to be seen whether the drug’s modest effect will persist for years.

    The committee also recommended more research on the drug’s efficacy in people of colour — more than 90% of Lilly’s trial participants were white — and people with Down’s syndrome or genetic mutations that make them more prone to ARIA. Committee member Kathleen Poston, a neurologist at Stanford University Medical Center in California, says scientists need to obtain these data “to make sure that these encouraging findings can be extrapolated to everyone with Alzheimer’s disease.” The FDA’s final decision is expected later this year.

    [ad_2]

    Source link

  • Ophthalmological method can be used to monitor neurodegeneration in Parkinson’s patients

    Ophthalmological method can be used to monitor neurodegeneration in Parkinson’s patients

    [ad_1]

    A study by the University of the Basque Country (UPV/EHU) and Biobizkaia proposes using an available, simple, non-invasive tool to monitor this neurodegeneration.

    Although there are still some aspects pending confirmation for its use in the clinical setting, and its resolution needs to be improved slightly, a study by the UPV/EHU and Biobizkaia has shown that a method routinely used to carry out ophthalmological tests can also be used to monitor the neurodegeneration that occurs in Parkinson’s patients. In the course of the research it was found that the neurodegeneration of the retina probably precedes cognitive impairment.

    When Parkinson’s or another neurodegenerative disease is diagnosed, patients always ask: “And now what? What will happen? What can be expected from the disease?” For neurologists, however, it is not possible to answer these questions precisely, as “the evolution of patients tends to be very varied: some experience no change over the years, while others end up with dementia or in a wheelchair”, explained Ane Murueta-Goyena, researcher in the UPV/EHU’s department of Neurosciences.

    Today, identifying Parkinson’s patients at risk of cognitive impairment poses a major challenge, yet this is necessary when it comes to providing more effective clinical treatments and stepping up clinical trials. In fact, Dr. Ane Murueta-Goyena, in collaboration with Biobizkaia’s research staff, wanted to see “whether the visual system can enable this deterioration to be predicted, in other words, what future the patient can expect within a few years”. The thickness of the retina was used for this purpose.

    The retina is a membrane located at the back of the eyeball, it is related to the nervous system and comprises several layers. During the study, a cohort of Parkinson’s patients had the thickness of the innermost layer of their retinas measured using optical coherence tomography. This type of tomography is a routinely used instrument in ophthalmological tests, as it allows high-resolution, repeatable and accurate measurements to be made. So the evolution of this retinal layer was analysed and compared in people with and without Parkinson’s disease over the 2015-2021 period. The results of the analysis of the images of the retinal layers of Parkinson’s patients were also confirmed in a UK hospital.

    The results showed that the retinal layer is noticeably thinner in Parkinson’s patients. It was also observed that “during the initial phases of the disease it is in the retina where the greatest neurodegeneration is detected, and, from a given moment onwards, when the layer is already very thin, a kind of stabilising of the neurodegeneration process takes place. Retinal thinning and cognitive impairment do not occur simultaneously. The initial changes in the retina are more evident and then, over the years, patients are observed to worsen clinically in both cognitive and motor terms”, explained Murueta-Goya. In other words, the slower retinal layer thickness loss is associated with faster cognitive decline; this slowness is linked to greater severity of the disease”.

    The researcher has attached great importance to the results: “We have obtained information on the progression of the disease, and the tool we are proposing is non-invasive and available at all hospitals.” The results need to be validated internationally and “by slightly improving the resolution of the technology, we will be closer to validating the method for monitoring the neurodegeneration that takes place in Parkinson’s disease”. The researcher also revealed that they are continuing the research on another cohort of patients and that funding is the key.

    Source:

    University of the Basque Country

    Journal reference:

    Murueta-Goyena, A., et al. (2024). Association of retinal neurodegeneration with the progression of cognitive decline in Parkinson’s disease. Npj Parkinson’s Disease. doi.org/10.1038/s41531-024-00637-x.

    [ad_2]

    Source link

  • Study identifies potential strategy to diminish the devastating impacts of traumatic brain injuries

    Study identifies potential strategy to diminish the devastating impacts of traumatic brain injuries

    [ad_1]

    For the roughly 1.5 million Americans per year who survive a traumatic brain injury, health outcomes vary widely. Not only can these injuries lead to a loss of coordination, depression, impulsivity, and difficulty concentrating, but they come with an amplified risk for developing dementia in the future.

    The glaring absence of treatments for such a widespread condition drove a team of scientists at Gladstone Institutes to uncover, on a molecular level, how traumatic brain injuries trigger neurodegeneration-;and just as importantly, how to target that process to prevent long-term damage.

    “We set out to address the fundamental question of exactly what happens in the brain after injury to ignite the damaging process that destroys neurons,” says Jae Kyu Ryu, PhD, a scientific program leader in the lab of Katerina Akassoglou, PhD at Gladstone Institutes.

    Most traumatic brain injuries come as a result of falls, car crashes, or violent assaults, according to the Centers for Disease Control, but many also stem from sports accidents or certain military operations such as explosions. In each case, the external force is strong enough to move the brain within the skull, causing a significant breakdown in the blood-brain barrier and allowing blood to move in.

    “We knew that a specific blood protein, fibrin, was present in the brain after traumatic brain injury, but we didn’t know until now that it plays a causative role in brain damage after injury,” says Ryu, who led the study that appears in the Journal of Neuroinflammation.

    Ryu and others in Akassoglou’s lab have long investigated how blood that leaks into the brain triggers neurologic diseases, essentially by hijacking the brain’s immune system and setting off a cascade of harmful, often-irreversible effects. Fibrin, a protein that normally helps blood coagulate, is the culprit. 

    Across many neurological diseases, toxic immune responses in the brain are triggered by blood leaks and drive neurodegeneration. Neutralizing the toxic immune responses in the brain paves the way to new therapies for neurological diseases.”


    Katerina Akassoglou, senior investigator at Gladstone and director of the Center for Neurovascular Brain Immunology at Gladstone and UCSF

    In diseases such as Alzheimer’s and multiple sclerosis, abnormal leaks in the protective blood-brain barrier allow fibrin to seep into areas responsible for cognitive and motor functions causing neurodegeneration. But in this case, the traumatic brain injury itself causes the blood to leak into the brain. The new study showed, for the first time, that fibrin is responsible for turning good immune cells bad, causing dangerous inflammation and unleashing toxins that kill neurons.

    The Gladstone team used state-of-the-art imaging technology to study mouse brains, as well as brains from people who experienced a traumatic brain injury. They also produced three-dimensional imaging of a whole intact mouse brain, showing blood-brain barrier leaks and abundant fibrin in traumatic brain injury. In both mouse and human brains, fibrin was present together with activated immune cells.

    “It became clear that fibrin is activating these immune cells,” Ryu says. “We realized that we can prevent the toxic effects if we could block fibrin, but we had to do it in a precise way.”

    The team leveraged genetic tools with a specific mutation in fibrin that can block it from activating immune cells without affecting the protein’s beneficial blood-clotting abilities. This is especially critical for traumatic brain injuries, as excessive bleeding into the brain has been known to occur among patients who were taking anticoagulant medications before their injury.

    Akassoglou’s lab previously developed a drug, a therapeutic monoclonal antibody, that acts only on fibrin’s inflammatory properties, without adverse effects on blood coagulation. This fibrin-targeting immunotherapy protects from multiple sclerosis and Alzheimer’s disease in mice. A humanized version of this first-in-class fibrin immunotherapy is already in Phase 1 safety clinical trials by Therini Bio.

    “It’s exciting to have a therapeutic option to neutralize blood toxicity in neurologic diseases,” Ryu says. “Future studies are needed to test the effects of the fibrin immunotherapy in traumatic brain injury.”

    “This study identifies a potential new strategy to diminish the devastating impacts of brain injuries,” says Lennart Mucke, MD, director of the Gladstone Institute of Neurological Disease. “Brain injuries can have profound effects on a person’s cognitive abilities, emotional health, and motor skills, touching every part of their life. It will be interesting to explore whether blocking the disease-promoting effects of fibrin can improve the outcome of brain surgeries and reduce disability when implemented after traumatic brain injuries have occurred.”

    Source:

    Journal reference:

    Dean, T., et al. (2024). Fibrin promotes oxidative stress and neuronal loss in traumatic brain injury via innate immune activation. Journal of Neuroinflammation. doi.org/10.1186/s12974-024-03092-w.

    [ad_2]

    Source link

  • Ancestral allele of DNA polymerase gamma modifies antiviral tolerance

    [ad_1]

    Ethical aspects

    Human samples were collected and used with informed consent, according to the Helsinki Declaration and approved by the Ethical Review Board of Kuopio University Central Hospital (410/2019). Animal experimental procedures were approved by the Animal Experimental Board of Finland (ESAVI/689/4.10.07/2015 and ESAVI/3686/2021). Patient and control materials included fibroblasts (established from skin biopsies from individuals’ forearms), blood and autopsy-derived brain samples. Control samples were from voluntary healthy individuals (fibroblasts and sera) and, for brains, from people who died acutely with a non-central-nervous-system-disease cause. Autopsy sample collection was approved by the governmental office for social topics and health.

    Antibodies, antisera and kits

    Information of the antibodies and oligonucleotide sequences is provided in Supplementary Table 6. Enzyme-linked immunosorbent assay (ELISA) kits for mouse IFNα all subtypes (42115-1), mouse IFNβ (42410-1), mouse IL-6 (BMS603HS), human IL-6 (BMS213HS) and human TNF (HSTA00E) and the CellTiter-Glo Luminescent Cell Viability Assay kit (Promega) were commercially purchased, and assays were performed according to the manufacturer’s instructions.

    MIRAS mouse generation

    MIRAS knock-in mice were generated and maintained in the C57BL/6JOlaHsd background carrying two variants homologous to mutations of patients with MIRAS on mouse chromosome 7 (NCBI Reference Sequence: NC_000073.7): c.2177G>C into exon 13 (p.W726S); c.3362A>G into exon 21 (p.E1121G). In brief, the pL253 construct carrying exons 4–22 of the Polg1 genomic region carrying the MIRAS variants was transfected into embryonic stem (ES) cells by electroporation and homologous recombination introduced to the endogenous gene. ES clones with successful recombination were selected based on neomycin resistance. The mutations were confirmed using Southern blot hybridization, PCR and DNA sequencing (DNA-seq). Correct ES clones were injected into blastocysts and implanted into pseudopregnant female mice. Lines with verified germ-line transmission were crossed with mice expressing FLP recombinase to remove the neomycin cassette. The correct genotypes of MIRAS mice were confirmed by DNA-seq. The genotypes were born in Mendelian frequencies, with no gross phenotypic differences between the groups. Mice were housed in controlled rooms at 22 °C under a 12 h–12 h light–dark cycle and with ad libitum access to food and water, and were regularly monitored for weight and food consumption. Further details are provided in Extended Data Fig. 6.

    Cell culture and transfection

    Human primary dermal fibroblasts (of the first 8 passages; ±2 passage difference across cell lines of different individuals) that were genetically screened for MIRAS point mutations (by DNA-seq) were used for analyses. Fibroblasts were cultured in DMEM (Lonza; with 4.5 g l−1 glucose) supplemented with 10% (v/v) heat-inactivated FBS (Lonza), 50 U ml−1 penicillin–streptomycin (Gibco), 0.05 mg ml−1 uridine (Calbiochem) and 2 mM GlutaMAX (Gibco) at 37 °C under 5% CO2, with fresh medium replaced every 2 days, and were tested negative for mycoplasma. Transfection of synthetic dsDNA50 and dsRNA (poly(I:C), Sigma-Aldrich) was performed using FuGENE HD transfection reagent (Promega). In brief, around 2 × 105 cells were plated onto six-well dishes the day before transfection and transfected with 2.5 μg of dsDNA or dsRNA per well with a 1:2 ratio of nucleic acid:transfection reagent, according to the manufacturer’s instructions (sequence details are provided in Supplementary Table 6). For expression of RIG-I or MAVS, fibroblasts were transfected with pcDNA3.1(+)-Flag containing RIG-I (N) or MAVS51 before poly(I:C) transfection 24 h later and incubated for another 7 h before collection.

    Patient genetic mutation correction in iPSCs

    For MIRAS POLG1 genetic correction, electroporation with CRISPR–Cas9 system components was performed as previously described52. We used high-efficiency gRNA and a dsDNA donor template including the desired correction along with a novel restriction site for SalI (GˆTCGAC). A total of 55 monoclonal colonies was individually screened by SalI digestion and successful correction was validated by Sanger sequencing. The chromosomal integrity was confirmed by G-banding performed by Anàlisis Mèdiques Barcelona. A list of the gRNA, donor template and primers for top-six off-target Sanger sequencing (CRISPOR, https://benchling.com) is provided in Supplementary Table 6.

    Differentiation of iPSCs into iFLCs

    Induced pluripotent stem cells (iPSCs) were cultured on Matrigel-coated (Corning) plates in E8 medium (Thermo Fisher Scientific) until 90–100% confluency, then split and plated in suspension in ultra-low attachment plates containing hES medium without basic fibroblast growth factor (bFGF) and supplemented with 5 µM ROCK inhibitor (Y-27632, Selleckchem). The medium without ROCK inhibitor was refreshed every other day until day 14, when the aggregates were plated onto gelatin-coated plates containing DMEM/F12 + 20% FBS (Thermo Fisher Scientific) to allow for expansion. The cells were kept for at least 5 passages to obtain induced fibroblast-like cells (iFLCs).

    qPCR

    RNA from cells was extracted using the RNeasy kit (Qiagen) according to the manufacturer’s instructions. For tissues, homogenization was first performed with ceramic beads using Precellys 24 homogenizer (Precellys) before RNA extraction using the Trizol/chloroform method followed by purification using the RNeasy kit. DNase-treated RNA (normalized across samples) was used for cDNA synthesis using the Maxima first-strand cDNA synthesis kit (Thermo Fisher Scientific) before qPCR using SensiFAST SYBR No-ROX kit (Bioline) and primers (details in Supplementary Table 6) according to the manufacturer’s instructions. The amplification level of the assayed gene (2–4 technical replicates per controls and patients) was normalized to ACTB and analysed using the \({2}^{-\Delta \Delta {C}_{{\rm{t}}}}\) method. mtDNA qPCR was performed on DNA extracted using the DNeasy blood and tissue kit (Qiagen) as described above and previously53 and normalized to nuclear ACTB or B2M. For viral RNA analyses, TBEV NS5 RNA54 or murine hepatitis virus55 RNA amount was detected using primers and Taqman probes against the targeted viral genome, using the TaqMan Fast Virus 1-Step Master Mix (Thermo Fisher Scientific) according to the manufacturer’s instructions. The copy number for TBEV NS5 RNA was determined using a standard curve generated by serial dilution of TBEV-isolated NS5 RNA. Details of the primers are provided in Supplementary Table 6.

    Cytosolic extraction and detection of cytosolic mtRNA/mtDNA

    Pelleted cells were resuspended in isolation buffer (20 mM HEPES-KOH pH 7.6, 220 mM mannitol, 70 mM sucrose, 1 mM EDTA, 1× protease inhibitor (Thermo Fisher Scientific)) and divided into two equal fractions: fraction 1, purify total cellular RNA or DNA; and fraction 2, subcellular fractionation to isolate cytosolic RNA or DNA. In brief, fraction 2 was homogenized in around 900 μl of suspension buffer in a handheld Dounce tissue homogenizer with glass pestle (~15 strokes). The homogenate was centrifuged at 800 g for 5 min at 4 °C and the resulting supernatant was centrifuged at 12,000 g for 10 min at 4 °C. The supernatants were collected and centrifuged at 17,000 g for 15 min at 4 °C to purify the cytosolic fraction. The whole-cell (fraction 1) and cytosolic (of fraction 2) fractions were subjected to DNA or RNA purification using the RNeasy Kit or DNAeasy Blood and Tissue Kit (Qiagen) and eluted into an equal volume of water. RNA eluate was treated with DNase before cDNA production. Equal volume of cDNA or DNA eluate were used for qPCR using nuclear gene primers (ACTB or B2M) or mitochondrial genome-specific primers (MT-CYB and MT-CO1). mtDNA/RNA abundance in whole cells served as normalization controls for their values obtained from cytosolic fractions18. The purity of cytosolic fraction was examined by western blotting.

    In vivo BrdU labelling and south-western analyses

    Mice receiving an intraperitoneal injection of 300 μg of BrdU (BD Biosiences) per gram of mouse weight were euthanized 24 h after injection. DNA was isolated by routine phenol–chloroform extraction. XhoI-digested DNA was separated using agarose gel electrophoresis and blotted onto Hybond N+ membranes (Amersham) as described previously53. Immunodetection was performed using anti-BrdU antibodies, and total mtDNA was detected using Southern hybridization as described previously56.

    Viral stocks and infections of fibroblasts

    The European subtype of TBEV was isolated from human neuroblastoma cells (SK-N-SH; passage 1) infected with tick collected in Finland57; SARS-CoV-2 was isolated from a patient with COVID-19 on human non-small cell lung cancer (Calu-1) cells58, passaged on African green monkey kidney (Vero E6) cells expressing type II membrane serine protease 2 (TMRSS2) via lentivirus transduction59; the KOS strain of herpes simplex virus 1, HSV-160, was passaged on Vero cells. SK-N-SH (https://www.atcc.org/products/htb-11), Calu-1 (https://www.atcc.org/products/htb-54), Vero E6 (https://www.atcc.org/products/crl-1586) and Vero (https://www.atcc.org/products/ccl-81) cells were purchased from ATCC. The virus work was performed under bio-safety level 3 (BSL-3) conditions for TBEV and SARS-CoV-2 and under BSL-2 conditions for HSV-1. The ability of viruses to infect fibroblasts was tested by inoculating cells grown on a 96-well plate with serially ten-fold diluted virus stocks and the optimal viral dilution was selected based on the dilution showing the most prominent difference in infected cells number between wild-type control and MIRAS cells using immunofluorescence.

    For fibroblast infection, around 2 × 105 fibroblast cells were grown on six-well plates the day before (or ~1 × 105 iFLCs 2 days before) being inoculated with 500 µl of 1:20 diluted TBEV, 1:10 diluted SARS-CoV-2 or 1:5,000 diluted HSV-1 (multiplicity of infection (MOI) of ~0.1–1). After 1 h (at 37 °C, 5% CO2), the inocula were removed, the cells were washed twice with conditioned medium, 3 ml of fresh medium was added to each well and the plates were incubated at 37 °C under 5% CO2 for 6, 24 or 48 h. Non-treated cells that were plated simultaneously alongside those subjected to viral infection were used as the uninfected control. At the end of incubation, the cells were washed twice with PBS and were lysed in RIPA buffer (50 mM Tris, 150 mM NaCl, 1% Triton X-100, 0.1% SDS, 0.5% sodium deoxycholate, pH 8.0) supplemented with EDTA-free protease inhibitor cocktail (Roche), at 150 µl per well for western blotting analyses. For DNA/RNA analyses, 60 µl of RIPA lysate was mixed with TRIzol Reagent (Thermo Fisher Scientific) before DNA or RNA extraction and RT–qPCR or qPCR as described in relevant Methods section. For the immunofluorescence assay, infected cells were fixed with 4% paraformaldehyde (PFA, in PBS) and incubated for 15 min at room temperature. The cells were washed once with PBS, permeabilized for 5 min at room temperature with Tris-buffered saline, pH 7.4 supplemented with 0.25% Triton X-100 and 3% (w/v) of bovine serum albumin, and replaced with PBS. Virus inactivation was confirmed by UV-inactivation with a dose of 500 mJ cm−2 before incubation with primary antibodies and processed as described below.

    Immunofluorescence microscopy

    The PFA-fixed viral-infected cells were stained with primary antibodies (Supplementary Table 6) overnight at 4 °C and for 1 h at room temperature with secondary antibodies. Three washes with PBS were included between each step. Coverslips were mounted with VECTASHIELD anti-fade mounting medium containing DAPI (Vector Laboratories). Images were acquired using the Zeiss AxioImager epifluorescence microscope. Quantification of the immunofluorescence signal was performed using CellProfiler (v.4.2.6)61.

    Gel electrophoresis and western blotting

    Cells lysed in RIPA buffer (150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, 0.1% SDS, 50 mM Tris-Cl, pH 8.0) were measured for protein concentration using the BCA assay (Pierce) and equal amounts of protein samples were resuspended into SDS–PAGE loading dye (50 mM Tris-Cl, pH 6.8, 100 mM dithiothreitol, 2% (w/v) sodium dodecyl sulphate, 10% (w/v) glycerol, 0.1% (w/v) bromophenol blue), boiled for 5–10 min at 95 °C before SDS–PAGE analysis using the 4–20% gradient gel (Bio-Rad) according to the manufacturer’s instructions.

    For mitochondrial protein analyses, mitochondria were isolated from tissue using differential centrifugation as described previously62. The clarified mitochondrial pellets were resuspended into buffer (20 mM HEPES-KOH pH 7.6, 220 mM mannitol, 70 mM sucrose, 1 mM EDTA) and analysed using SDS–PAGE, or solubilized using 1% (w/v) n-dodecyl-β-d-maltoside (DDM) in 1.5 M α-amino n-caproic acid for 30 min on ice for blue-native (BN) electrophoresis analysis. DDM-solubilized samples were centrifuged at 20,000g for 20 min at 4 °C. The clarified supernatants were measured for protein concentration using the BCA assay and equal amounts of protein samples were mixed with BN loading dye (0.25% (w/v) Coomassie blue G250 (MP Biomedicals), 75 mM α-amino n-caproic acid) before BN electrophoresis using cathode buffer (50 mM tricine, 15 mM Bis-Tris, pH 7.0, 0.02% (w/v) Coomassie blue G250) and anode buffer (50 mM Bis-Tris, pH 7.0) on self-casted 1-mm-thick 5–12% gradient polyacrylamide gels. Separation part of the gel was prepared by mixing solution of 5 and 12% acrylamide (acrylamide:bisacrylamide 37.5:1) in 0.5 M α-amino n-caproic acid, 50 mM Bis-Tris (pH 7.0), 11 or 20% (w/v) glycerol, 0.027% ammonium persulfate, 0.1% TEMED. Separation gel was overlayed with a 4% acrylamide stacking gel solution as described above (no glycerol; but 0.084% ammonium persulfate, 0.17% TEMED).

    After electrophoresis, gels were transferred onto 0.45 μm PVDF membranes using a semidry transfer (SDS–PAGE) or wet transfer (BN-PAGE) apparatus (Bio-Rad) before western blotting using the desired antibodies (details are provided in Supplementary Table 6). Images were obtained using ChemiDoc XRS+ imaging machine (Bio-Rad) and signals were quantified using Image Lab (v.6.1.0 build 7; Bio-Rad) according to the manufacturer’s instructions. The protein-of-interest signal was normalized to the loading control signal in the sample.

    Mouse behavioural analyses

    Treadmill

    An Exer-6M treadmill (Columbus Instrument) was used as described previously63. The tests were completed as a set of five independent trials over 1 h. The running time was counted when the mouse stopped for five continuous seconds and did not continue.

    Rotarod

    The rotating rod system (Rota-Rod; Ugo Basile, 47600) with a PVC drum (diameter of 44 mm) was used as described previously64. The animals were trained for three consecutive days before the test.

    Footprint analyses to detect ataxia

    Mouse feet were painted with non-toxic washable paint (separate colours for hind- and forelimbs) and the mouse was allowed to walk through a tunnel on paper. The stride length and width were measured. Scoring data were obtained using at least two consecutive steps from each foot.

    Infection of mice, histology and immunohistochemistry

    Mice were transported to the BSL-3 facility and acclimatized to individually ventilated biocontainment cages (ISOcage; Scanbur) for 7 days before being inoculated intraperitoneally with 1,000 plaque-forming units of TBEV. Mice were euthanized at the indicated days after infection and sera were collected for cytokine analyses using commercially purchased ELISA kits (see the ‘Antibodies, antisera and kits’ section). For DNA, RNA or protein analyses (see the relevant Methods section), tissues were collected into TRIzol Reagent (Thermo Fisher Scientific). For histology, liver samples were fixed in cold 4% (v/v) PFA in PBS and incubated in PBS supplemented with 30% (w/v) sucrose at 4 °C for 3 days before routine embedding in OCT compound and trimmed into sections with a thickness of 6–8 μm for haematoxylin and eosin or ORO staining according to the standard protocol65. For immunohistochemical staining, liver sections were stained with the following antibodies: CD3 (T cell marker), CD4 (helper T cell marker), CD8b (cytotoxic T cell marker) or CD68 (macrophage marker) using the ImmPRESS HRP goat anti-rat IgG (Mouse Adsorbed) Polymer Kit (Vector Laboratories, MP-7444), and with haematoxylin counterstaining according to the manufacturer’s instructions. Liver inflammation severity was semi-quantitatively scored and the total number of immune cell infiltrations was quantified from three unique visual fields at ×5 magnification (15,370,559 μm2 per view) per mouse liver section. The area (μm2) of the largest infiltrate detected per view was measured using ImageJ (2.0.0-rc-69/1.52n; https://imagej.net/ij/). Liver ORO and CD protein signal was quantified using CellProfiler (v.4.2.6)61 after pixel classification using ilastik (v.1.3.3)66.

    For brain histology, brain halves (cut in midline) were fixed in PFA for 48 h, then stored in 70% (v/v) alcohol until processing. They were trimmed and routinely paraffin-wax embedded. Consecutive sections (3–4 µm) were prepared and stained with haematoxylin and eosin or subjected to immunohistochemical staining for TBEV antigen, CD3 (T cell marker), CD45R/B220 (B cell marker) and IBA1 (marker of macrophages and microglial cells), according to previously published protocols67,68. Mouse brain GABAergic marker staining was performed using GAD67 and GABRB2 antibodies followed by blinded semi-quantitative scoring by A.P. (neuropathologist). Details of the antibodies are provided in Supplementary Table 6.

    Bulk RNA-seq analysis

    RNA-seq was performed at the Biomedicum Functional Genomics Unit (University of Helsinki) according to the Drop-seq protocol as described previously69,70. A total of 10 ng of extracted RNA was used as the starting material. The quality of the sequencing libraries was assessed using the TapeStation DNA High Sensitivity Assay (Agilent). The libraries were sequenced on the Illumina NextSeq 500 system70. For read alignment and generation of digital expression data, raw sequencing data were inspected using FastQC and multiQC71,72. Subsequently, reads were filtered to remove low-quality reads and reads shorter than 20 bp using Trimmomatic73. Reads passing the filter were then processed further using Drop-seq tools according to the pipeline described69 (v.2.3.0). In brief, the raw, filtered read libraries were converted to sorted BAM files using Picard tools (http://broadinstitute.github.io/picard). This was followed by tagging reads with sample specific barcodes and unique molecular identifiers (UMIs). Tagged reads were then trimmed for 5′ adapters and 3′ poly A tails. Alignment ready reads were converted from BAM-formatted files to fastq files that were used as an input for STAR aligner74. Alignments were performed using the GRCm38 (mouse) reference genome and GENCODE mouse release 28 or the GRCh38 (human) reference genome and GENCODE human release 33 comprehensive gene annotation files75 with default STAR settings. After the alignment, the uniquely aligned reads were sorted and merged with the previous unaligned tagged BAM file to regain barcodes and UMIs that were lost during the alignment step. Next, annotation tags were added to the aligned and barcode-tagged BAM files to complete the alignment process. Finally, Drop-seq tools were used to detect and correct systematic synthesis errors present in sample barcode sequences. Digital expression matrices were then created by counting the total number of unique UMI sequences (UMI sequences that differ by only a single base were merged together) for each transcript. Differential expression analysis was performed with DESeq2 (using the default settings) in the R environment76.

    Untargeted metabolomics

    Metabolites were extracted from 20 mg of mouse cerebral cortex in hot ethanol. In brief, frozen samples were homogenized in 0.5 ml 70% (v/v) ethanol with ceramic beads using a Precellys 24 homogenizer (Precellys). Before and after homogenization, the samples were kept frozen (at ≤−20 °C). The samples were transferred to a 15 ml tube with washing using 0.5 ml of 70% (v/v) ethanol. To each tube, we added 7 ml of 70% (v/v) ethanol that was preheated at 75 °C, immediately vortexed and placed the sample into a water bath at 75 °C for 1 min followed vortexing once. The content was cooled down in cold bath at −20 °C before being centrifuged for 10 min (4 °C). The clear supernatant was transferred to a new tube and stored at −80 °C until analysis using mass spectrometry (MS).

    Untargeted metabolite profiling was performed using flow injection analysis on the Agilent 6550 QTOF instrument (Agilent) using negative ionization, 4 GHz high-resolution acquisition and scanning in MS1 mode between m/z 50 and m/z 1,000 at 1.4 Hz. The solvent was 60:40 isopropanol:water supplemented with 1 mM NH4F at pH 9.0, as well as 10 nM hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine and 80 nM taurochloric acid for online mass calibration. The seven batches were analysed sequentially. Within each batch, the injection sequence was randomized. Data were acquired in profile mode, centroided and analysed using MATLAB (MathWorks). Missing values were filled by recursion in the raw data. After identification of consensus centroids across all of the samples, ions were putatively annotated by accurate mass and isotopic patterns. Starting from the HMDB v.4.0 database, we generated a list of expected ions including deprotonated, fluorinated and all major adducts found under these conditions. All formulas matching the measured mass within a mass tolerance of 0.001 Da were enumerated. As this method does not use chromatographic separation or in-depth MS2 characterization, it is not possible to distinguish between compounds with an identical molecular formula. The confidence of annotation reflects level 4 but, in practice, in the case of intermediates of primary metabolism, it is higher because they are the most abundant metabolites in cells. The resulting data matrix included 1,943 ions that could be matched to deprotonated metabolites listed in HMDB v.3.0.

    Proteomics

    Protein was extracted from 50 mg of frozen brain autopsy samples using TRIzol Reagent (Thermo Fisher Scientific) according to the manufacturer’s instructions. Extracted protein pellets were resuspended into 100 μl of buffer containing 6 M urea, 50 mM ammonium bicarbonate, pH 8 and boiled for 5–10 min at 95 °C. The protein concentration was estimated using the BCA assay (Pierce) and equal amounts of protein samples were aggregated on amine beads77. For on-bead digestion, 50 mm ammonium bicarbonate buffer was added to the beads. Proteins were reduced with 10 mM DTT for 30 min at 37 °C and alkylated with 20 mM IAA for 30 min at room temperature in dark, after which 0.5 µg of trypsin was added, and trypsin digestion was performed overnight at 37 °C. Beads were separated using a magnet, the supernatant was transferred to new tube and acidified, and the tryptic peptides were desalted using C18 StageTips for MS analysis. Liquid chromatography coupled with tandem MS (LC–MS/MS) analysis of the resulting peptides was performed using the Easy nLC1000 liquid chromatography system (Thermo Electron) coupled to a QExactive HF Hybrid Quadrupole-Orbitrap mass spectrometer (Thermo Electron) with a nanoelectrospray ion source (EasySpray, Thermo Electron). The LC separation of peptides was performed using the EasySpray C18 analytical column (2 µm particle size, 100 Å, 75 μm inner diameter and 25 cm length; Thermo Fisher Scientific). Peptides were separated over a 90 min gradient from 2% to 30% (v/v) acetonitrile in 0.1% (v/v) formic acid, after which the column was washed using 90% (v/v) acetonitrile in 0.1% (v/v) formic acid for 20 min (flow rate 0.3 μl min−1). All LC–MS/MS analyses were operated in data-dependent mode where the most intense peptides were automatically selected for fragmentation by high-energy collision-induced dissociation. For data analysis, raw files from LC–MS/MS analyses were submitted to MaxQuant (v.1.6.7.0)78 for peptide/protein identification and label-free quantification. Parameters were as follows: carbamidomethyl (C) was set as a fixed modification; protein N-acetylation and methionine oxidation as variable modifications; first search error window of 20 ppm and main search error of 6 ppm; the trypsin without proline restriction enzyme option was used, with two allowed miscleavages; minimal unique peptides was set to one; and the FDR allowed was 0.01 (1%) for peptide and protein identification. The UniProt human database (September 2018) was used for the database searches. MaxQuant output files (proteinGroups.txt) were loaded into Perseus (v.1.6.1.3)79 for further data filtering and statistical analysis. Identifications from potential contaminants and reversed sequences were removed, and normalized intensities (LFQ) were log10-transformed. Next, a criteria of at least 50% valid values in at least one group was used to filter the results. All zero intensity values were replaced using noise values of the normal distribution of each sample. Protein abundances were compared using a two-sample Student’s t-test with P < 0.05 as the criteria for a statistically significant difference between the two groups.

    Functional and pathway enrichment analyses

    Qiagen Ingenuity Pathway Analyses (Qiagen; https://digitalinsights.qiagen.com/IPA), g:Profiler80 (https://biit.cs.ut.ee/gprofiler) toolset and KEGG database81 were used for the analyses of transcriptome, metabolome and/or proteome datasets. For immune pathway analyses, we further used the manually curated InnateDB database82 (https://www.innatedb.com/index.jsp).

    Genotype–phenotype association analyses

    Analyses were performed on the data from the FinnGen study, a large-scale genomics initiative that has analysed Finnish Biobank samples and correlated genetic variation with health data to understand disease mechanisms and predispositions6. The mixed-model logistic regression method SAIGE (R package developed with Rcpp for genome-wide association tests in large-scale datasets and biobanks) was used for association analysis and included the following covariates in the model: sex, age, genotyping batch and ten principle components. These results are from 3,095 end points, 16,962,023 variants and 309,154 individuals in data freeze 7 (https://r7.finngen.fi/).

    Statistical analyses

    Statistical analyses as described in the figure legends were performed either using Microsoft Excel v.16.80, GraphPad Prism v.10.1.1 for macOS (GraphPad, www.graphpad.com) or using toolsets as indicated in the respective figure legends and in relevant method sections. GraphPad Prism v.10.1.1 as described above was used to create box and whisker plots using the standard five-number summary: minimum, lower quartile (25th percentile), median (50th percentile), upper quartile (75th percentile) and maximum, with whiskers extending down to the minimum and up to the maximum value; bar charts show the mean ± s.e.m. The datapoints for each value are superimposed on the plot. No statistical methods were used to predetermine the sample size. Sample sizes were chosen to ensure adequate power and to account for potential interindividual/animal, gender and age variance (age- and sex-matched samples were used as controls). The number of biologically independent mouse or human samples is described in the respective figure legends.

    Reporting summary

    Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

    [ad_2]

    Source link

  • Diabetes drug slows development of Parkinson’s disease

    Diabetes drug slows development of Parkinson’s disease

    [ad_1]

    A diabetes drug related to the latest generation of obesity drugs can slow the development of the symptoms of Parkinson’s disease, a clinical trial suggests1. Participants who took the drug, called lixisenatide, for 12 months showed no worsening of their symptoms — a gain in a condition marked by progressive loss of motor control.

    Further work is needed to control side effects and determine the best dose, but researchers say that the trial marks another promising step in the decades-long effort to tackle the common and debilitating disorder.

    “This is the first large-scale, multicentre clinical trial to provide the signs of efficacy that have been sought for so many years,” says Olivier Rascol, a Parkinson’s researcher at Toulouse University Hospital in France, who led the study.

    The diabetes connection

    Lixisenatide is a glucagon-like peptide-1 (GLP-1) receptor agonist, making it part of a large family of similar compounds used to treat diabetes and, more recently, obesity. (The weight-loss drug semaglutide, sold under the brand name Wegovy, is a GLP-1 compound.)

    Many studies have shown a link between diabetes and Parkinson’s2. People with diabetes are around 40% more likely to develop Parkinson’s. And people who have both Parkinson’s and diabetes often see more rapid progression of symptoms than do those who have only Parkinson’s.

    Animal studies3 have suggested that some GLP-1 drugs, which influence levels of insulin and glucose, can slow the symptoms of Parkinson’s. Smaller trials, published in 20134 and 20175, suggested that the GLP-1 molecule exenatide, another diabetes drug, could do the same in people.

    Progression halted

    In the latest, larger study, the French researchers investigated lixisenatide in 156 people with mild to moderate Parkinson’s symptoms, all of whom were already taking the standard Parkinson’s drug levodopa or other drugs. Half got the GLP-1 drug for a year and the others received a placebo.

    After 12 months, those in the control group showed a worsening of their symptoms. Specifically, their score had increased by three points on a scale used to assess the severity of Parkinson’s that measures how well people can perform tasks including speaking, eating and walking.

    Those taking the drug had no change in their scores on this scale. But the treatment did induce side effects. Nausea occurred in nearly half, and vomiting in 13%, of people on the medication. The results are published in The New England Journal of Medicine.

    Not a miracle drug

    David Standaert, a neurologist at the University of Alabama at Birmingham, who was not involved in the trial, says it’s important to know whether the effect will last beyond a year.

    “We’re all cautious. There’s a long history of trying different things in Parkinson’s that ultimately didn’t work,” he says. A difference of three points in the rating score is a small change — one that many people with Parkinson’s would struggle to notice, he says. “What happens at 5 years? Is it 15 points then, or is it still 3? If it’s still 3, then this is not worth it.”

    Lixisenatide as a diabetes treatment was pulled from the US market last year by its Paris-based manufacturer Sanofi for commercial reasons. But Standaert says that this would not have affected development of a possible treatment for Parkinson’s, because other GLP-1 drugs are available.

    Obesity drugs have another superpower: taming inflammation

    “I view this as a study of the class. I don’t know if this particular one is the right answer,” he says. Newer GLP-1 drugs (lixisenatide was developed in the 2000s) could offer fewer and milder side effects or work at lower doses, he adds.

    Another question that needs further consideration is just how some GLP-1 drugs might protect against Parkinson’s. The compounds are known to reduce inflammation, which has led some researchers to suggest that they prevent the steady loss of dopamine-producing neurons that drives the condition. That would offer a significant benefit over existing treatments such as levodopa, which mask the symptoms but don’t address the underlying cause. But this trial and others haven’t assessed neuron loss.

    Researchers are now waiting for the results of a large clinical trial examining the effects of a two-year course of exenatide in people with Parkinson’s disease. Those data will be available in the second half of this year, according to Tom Foltynie, a neurologist at University College London, in comments provided to the UK Science Media Centre.

    [ad_2]

    Source link