Author Archives: jpnd

A new, publicly accessible website is cataloguing the range of animal and cellular models currently available for the study of Parkinson’s disease (PD) and providing a forum for scientists to discuss the limitations of these models and how they might be improved. The JPND database of Experimental Models for Parkinson’s disease, developed in cooperation with the Italian Ministry of Education, Universities and Research (MIUR), aims to build an online network of scientists working in the field to more rapidly establish community consensus around currently available models. By bringing together expertise from across national and disciplinary boundaries, JPND seeks to accelerate progress toward the next generation of experimental models, which could ultimately contribute to a deeper understanding of the causes of PD and the development of potential disease-modifying therapies.

 

Why experimental models for Parkinson’s?

Experimental models mimic the processes thought to be at play in human patients and allow researchers to assess possible treatments before moving into clinical trials. They span both in vivo models – including mammals (e.g., mice) and non-mammals (e.g., zebrafish, Drosophila) — and in vitro models (e.g., “brain in a dish”). As such, they are a critical tool for scientists studying the origins and pathways of PD. Yet to date the available models have shown limited capabilities to translate the wealth of information recently generated by preclinical research into new treatments, diagnostics and preventive strategies. A 2014 report published by the JPND Action Group on Experimental Models identified some of the most pressing limitations facing current models for PD, including lack of behavioral analysis relevant to humans, lack of models for symptoms that do not respond to dopaminergic treatment, and lack of models with progressive neuronal loss associated to alpha-synuclein deposits and neuroinflammatory processes. With this web forum, JPND aims to address and expand on this analysis and set the basis for the development of innovative new strategies that can be applied in the field.

 

How does it work?

Sign up for free to access an overview of the different models and to join the conversation. The database currently provides detailed information on in-vivo mammalian models, and will soon be expanded to include non-mammalian in-vivo models as well as in vitro models. You may comment on specific individual models or categories of models and respond to comments already left by other users.  It is expected to be expanded over time, with other neurodegenerative diseases covered by JPND added progressively. Additional models will also be added thanks to your contribution; your participation will help to build an open source of information available to everyone.

 

Why join the forum?

  • Discuss the limitations and potential improvements of current models with other scientists
  • Get the latest updates on the state-of-the-art of experimental models for PD
  • Participate in real-time discussion

 

Join us at: https://www.neurodegenerationresearch.eu/models-for-parkinsons-disease/

 

For more information, please contact [email protected]

 

Scientists are reporting that monkeys with Parkinson’s disease symptoms show significant improvement over two years after being transplanted neurons prepared from human iPS cells. The study, published in Nature, is an expected final step before the first iPS cell-based therapy for neurodegenerative diseases.

Parkinson’s disease damages a specific type of cell in the brain known as dopaminergic (DA) neurons. It is known that by the time symptoms are first detected, a patient will have already lost more than half of his or her DA neurons. Several studies have shown the transplantation of DA neurons made from fetal cells can mitigate the disease. The use of fetal tissues is controversial, however. On the other hand, iPS cells can be made from blood or skin.

To test the safety and effectiveness of DA neurons made from human iPS cells, researchers transplanted the cells into the brains of monkeys.

It is generally assumed that the outcome of a cell therapy will depend on the number of transplanted cells that survive, but the scientists found this was not the case. More important than the number of cells was the quality of the cells.

To understand why, the team looked for genes that showed different expression levels, finding 11 genes that could mark the quality of the progenitors.

Another feature of the study that is expected to extend to clinical study is the method used to evaluate cell survival in the host brains. The study demonstrated that magnetic resonance imaging (MRI) and position electron tomography (PET) are options for evaluating the patient post-surgery.

Paper: “Human iPS cell-derived dopaminergic neurons function in a primate Parkinson’s disease model

Reprinted from materials provided by the Center for iPS Cell Research and Application – Kyoto University.

New research suggests serotonin loss may be a key player in cognitive decline, rather than a side-effect of Alzheimer’s disease.

In a study examining the brain scans of people with mild loss of thought and memory ability, researchers report evidence of lower levels of the serotonin transporter — a natural brain chemical that regulates mood, sleep and appetite. Previous studies have shown that people with Alzheimer’s disease and severe cognitive decline also have severe loss of serotonin neurons, but the studies did not show whether those reductions were a cause or effect of the disease. Results of the new study of people with very early signs of memory decline, the researchers say, suggest that lower serotonin transporters may be drivers of the disease rather than a byproduct.

A report on the study, published in Neurobiology of Disease, also suggest that finding ways to prevent the loss of serotonin or introducing a substitute neurotransmitter could slow or stop the progression of Alzheimer’s disease and perhaps other dementias.

To further study serotonin’s role in cognition and neurodegenerative disease, the research team used brain positron emission tomography (PET) scans to look at levels of serotonin in the brains of people with mild cognitive problems, which may be a precursor of Alzheimer’s disease or other dementias.

The study paired 28 participants with mild cognitive impairment with 28 healthy matched controls. Participants were an average age of 66 and about 45 percent were women. Each participant underwent an MRI and PET scan to measure brain structures and levels of the serotonin transporter SERT.  The researchers found that people with mild cognitive impairment had up to 38 percent less SERT detected in their brains compared to each of their age-matched healthy controls. And not a single person with mild cognitive impairment had higher levels of SERT compared to their healthy control.

Each participant also underwent learning and memory tests. On a scale of 0 to 80, with 80 reflecting the best memory, the healthy participants had an average score of 55.8, whereas those with mild cognitive impairment scored an average of 40.5.

With the Brief Visuospatial Memory Test, participants were shown a series of shapes to remember and draw later. From a scale of 0 to 36, with 36 being the top score, healthy people scored an average of 20.0 and those with mild cognitive problems scored an average of 12.6.

The researchers then compared the results from the brain imaging tests for the serotonin transporter to those two memory tests, and found that the lower serotonin transporters correlated with lower scores. For example, those people with mild cognitive impairment had 37 percent lower verbal memory scores and 18 percent lower levels of SERT in the brain’s hippocampus compared to healthy controls.

Paper: “Molecular imaging of serotonin degeneration in mild cognitive impairment

Reprinted from materials provided by Johns Hopkins University.

A new kind of antibody targets a feature shared by proteins thought to cause the most damage in Alzheimer’s disease, Parkinson’s disease, and related conditions, creating potential for a unified treatment approach. The findings are part of a study published online in Scientific Reports.

The new study builds on decades of work arguing that the contribution to disease of key proteins — amyloid beta and tau in Alzheimer’s, alpha-synuclein in Parkinson’s, and prion proteins in conditions like mad cow disease — is driven by certain, toxic forms dominated by a common structure: bundles of « beta sheets » in clumped proteins.

In tissues from autopsied patients with these diseases and in live mice, experiments demonstrated how the study’s antibodies target and remove only these toxic forms without triggering the immune toxicity that has stymied treatment development efforts to date.

The study focuses on proteins that form important structures in the brain. The instant they form as chains of amino acids, proteins fold into complex shapes needed to do their jobs. However proteins can also « misfold » and eventually cause disease. Cells and tissues die as misshapen proteins stop working and build up, but the field has struggled to pinpoint which of these shifting forms to target as the key drivers.

The researchers designed their antibodies to target the « oligomers » formed as several misfolded monomers associate and acquire the « beta-sheet » shape, but before they are large enough to fibrilize. These intermediate forms may be uniquely toxic because, unlike fibrils, they can dissolve and move in and out of cells, and from one cell to another. This mobility may explain the « prion-like » progression seen in misfolding diseases where abnormal proteins cause normal ones to misfold in a domino effect that damages nerve cells and their connections in the brain.

Importantly, growing toxic oligomers of amyloid beta, tau, alpha synuclein, and prion protein become increasingly dominated by twisted strands of amino acids, the beta sheet spatial arrangements that let the strands stack up.

To design new kinds of antibodies, the research team zeroed in on a small 13-amino-acid peptide, derived from the extremely rare genetic disease called British amyloidosis, but not present in the rest of the human population. They converted it into large, stable oligomer with more than 90 percent « beta-sheet » structure (the p13Bri immunogen) that could now be « seen » by the mammalian immune system. It also triggered a specific antibody response that solved problems encountered with standard approaches. By immunizing mice with p13Bri at high doses, they forced the production of extremely rare antibodies against beta sheets in toxic oligomers.

The researchers say that their rare antibodies, activated by protein fragments seen only in a rare disease, have almost zero chance of triggering unwanted immune responses to normal proteins with similar sequences (autotoxicity), the downfall of many previous attempts. Finally, the team screened their lead antibodies against tissues taken from the brains of human patients with Alzheimer’s, Parkinson’s and prion diseases. Only the six monoclonal antibodies that reacted to toxic oligomers from at least two misfolded proteins from two diseases were selected for further study.

Paper: “Production of Monoclonal Antibodies to Pathologic β-sheet Oligomeric Conformers in Neurodegenerative Diseases

Reprinted from materials provided by NYU Langone Health / NYU School of Medicine.

New artificial intelligence research has demonstrated the predictive capability of AI to determine in advance who is likely to develop dementia.

Scientists used artificial intelligence techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain of patients at risk of developing Alzheimer’s disease. Their findings appear in a new study published in the journal Neurobiology of Aging.

Scientists have long known that a protein known as amyloid accumulates in the brain of patients with mild cognitive impairment (MCI), a condition that often leads to dementia. Though the accumulation of amyloid begins decades before the symptoms of dementia occur, this protein couldn’t be used reliably as a predictive biomarker because not all MCI patients develop Alzheimer’s disease.

To conduct their study, the researchers drew on data available through the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a global research effort in which participating patients agree to complete a variety of imaging and clinical assessments.

The researchers used hundreds of amyloid PET scans of MCI patients from the ADNI database to train the team’s algorithm to identify which patients would develop dementia, with an accuracy of 84%, before symptom onset.

While new software has been made available online to scientists and students, physicians won’t be able to use this tool in clinical practice before certification by health authorities.

Paper: « Identifying incipient dementia individuals using machine learning and amyloid imaging »

Reprinted from materials provided by McGill University.

Alzheimer’s disease manifest itself with widely divergent symptoms and, so far, its various expressions have mainly been observed through the behaviour and actions of patients. Researchers have now produced images showing the changes in the brain associated with these symptoms — a development which increases knowledge and could facilitate diagnosis and treatment in the future.

Symptoms vary in cases of Alzheimer’s disease and often relate to the phase of life in which the disease first occurs. People who become ill before the age of 65 often suffer early on from diminished spatial perception and impaired orientation. Elderly patients more often suffer the symptoms traditionally associated with the disease: above all, memory impairment.

Diagnostics could be facilitated, mainly among younger patients in whom it is particularly difficult to arrive at a correct diagnosis.

The findings, published in the journal Brain, are based on studies of around 60 Alzheimer’s patients and a control group consisting of 30 people with no cognitive impairment.

This new imaging method can clearly detect clumps of the tau protein, which forms lumps and destroys the transport route of the neurons once Alzheimer’s disease has taken hold.

The method uses a device known as a PET camera and a trace substance, a particular molecule, which binds to tau. The imaging method is currently only used in research, where the current study is one of several contributing to increased knowledge about the disease.

Paper: “Distinct 18F-AV-1451 tau PET retention patterns in early- and late-onset Alzheimer’s disease »

Reprinted from materials provided by Lund University.

A large, long-term study suggests that middle-aged people who have vascular health risk factors, including diabetes, high blood pressure and smoking, have a greater chance of suffering from dementia later in life. The study was published in JAMA Neurology.

The study analyzed the data of 15,744 people. From 1987-1989, the participants, who were black or white and 45-64 years of age, underwent a battery of medical tests during their initial examinations. Over the next 25 years they were examined four more times. Cognitive tests of memory and thinking were administered during all but the first and third exams.

Researchers found that 1,516 participants were diagnosed with dementia during an average of 23 follow-up years. Initially, when they analyzed the influence of factors recorded during the first exams, the researchers found that the chances of dementia increased most strongly with age followed by the presence of APOE4, a gene associated with Alzheimer’s disease. Whites with one copy of the APOE4 gene had a greater chance of dementia than blacks. Other factors included race and education: blacks had higher chance of dementia than whites; those who did not graduate from high school were also at higher risk.

In agreement with previous studies, an analysis of vascular risk factors showed that participants who had diabetes or high blood pressure, also called hypertension, had a higher chance of developing dementia. In fact, diabetes was almost as strong a predictor of dementia as the presence of the APOE4 gene.

Unlike other studies, the researchers discovered a link between dementia and prehypertension, a condition in which blood pressure levels are higher than normal but lower than hypertension. Also, race did not influence the association between dementia and the vascular risk factors they identified. Diabetes, hypertension and prehypertension increased the chances of dementia for white and black participants. Finally, smoking cigarettes exclusively increased the chances of dementia for whites but not blacks.

Paper: “Associations Between Midlife Vascular Risk Factors and 25-Year Incident Dementia in the Atherosclerosis Risk in Communities (ARIC) Cohort »

Reprinted from materials provided by the NIH/NINDS.

People who get less rapid eye movement (REM) sleep may have a greater risk of developing dementia, according to a new study published in the August 23, 2017, online issue of Neurology. REM sleep is the sleep stage when dreaming occurs.

There are five stages of sleep, ranging from light sleep to deep sleep to REM sleep. During this dream stage, the eyes move rapidly and there is increased brain activity as well as higher body temperature, quicker pulse and faster breathing. The first REM stage occurs about an hour to an hour-and-a-half into sleep and then recurs multiple times throughout the night as the cycles repeat.

For the study, researchers looked at 321 people with an average age of 67 over the course of 12 years on average. Researchers collected the participants’ sleep data. Over the course of the study, 32 people were diagnosed with some form of dementia, 24 of whom were diagnosed with Alzheimer’s disease.

Those who developed dementia spent less time in REM sleep: an average of 17 percent, compared to 20 percent for those who did not develop dementia. After adjusting for age and sex, researchers found links between both a lower percentage of REM sleep and a longer time to get to the REM sleep stage and a greater risk of dementia. In fact, for every percent reduction in REM sleep there was a 9 percent increase in the risk of dementia. The results were similar after researchers controlled for other factors that could affect dementia risk or sleep, such as heart disease factors, depression symptoms and medication use.

Other stages of sleep were not associated with an increased dementia risk.

Paper: “Sleep architecture and the risk of incident dementia in the community »

Reprinted from materials provided by the American Academy of Neurology.