Monthly Archives: November 2021

An RNA surprise

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As usual, some background may be helpful here: You’ve heard of genomics, the analysis of large numbers of gene variants as a clue to disease causation.  But genomics doesn’t deal with the actual proteins produced by those genes.  That led to proteomics, the analysis of proteins in a tissue or fluid sample, as a more relevant window into disease mechanisms and possibly as a path to diagnostic tests.  But proteins in samples can be influenced by many things such as breakdown of proteins by enzymes or by the cells’ normal garbage disposal mechanisms.  A solution is “transcriptomics,” which identifies and quantifies messenger RNA (mRNA) on its way from being encoded (“transcribed”) by DNA to being translated into protein.  Although every cell in our bodies has our entire genetic endowment in the form of DNA, only a fraction of those genes is actually transcribed into mRNA.  The types and amounts of mRNA produced depend on the job of the specific cell and its protein needs at the moment.  Click here if you’d like to chew on a highly technical but excellent, current review of the topic.

In the current issue of the prestigious Journal of Clinical Investigation, a team mostly from the Mayo Clinic Jacksonville has compared the transcriptomes of tissue from cerebrum and cerebellum with autopsy-confirmed PSP to those with Alzheimer’s disease and to controls with no autopsy evidence of neurodegenerative disease.  I’ll cut to the chase:  To the researchers’ surprise, they found the four types of tissue to be quite similar in their transcriptomic profiles.  This result suggests that a treatment or a diagnostic test directed at one or more of the protein (or mRNA!) abnormalities in either disease could work for the other disease as well.  We already suspected that, but without a lot of supporting evidence beyond the superficial observation that both diseases involve tau aggregation.  This new paper provides some better evidence.

I’ll return to the paper’s practical implications in a minute.  But first, back to biology class you go: “O-omics” results (Wikipedia lists 45 kinds of “omics” in biomedicine to date) are by their nature shotgun approaches, typically yielding a long, inscrutable list of statistically significant but questionably meaningful differences between subject groups.  So, seeking some sort of useful pattern in the data, researchers divide the genes, proteins or mRNAs yielding statistically significant “hits” into categories based on their known functions.  These categories are called “networks” because they’re based on interactions or on commonalities of function.  The process of creating and using such standardized, defined categories in genomics is called “gene ontology.”

The authors of the new paper point out that previous transcriptomic work in AD has revealed differences from controls in many such networks, most prominently “immune function, myelination, synaptic transmission and lipid metabolism.”  They also point out that it’s usually difficult to know if these mRNA differences are the cause of the cellular damage in AD or merely the brain’s reactions to that damage.

Now back to this project:  As I said above, the transcriptomic work analyzed not only the cerebral cortex, where the researchers knew ample pathology exists in both AD and PSP, but also, as a kind of control group, the cerebellar cortex, where the standard autopsy shows little or no damage in AD or PSP.  Another feature of the study design was to use the temporal lobe as the source of its cerebral samples.  That part of the brain is heavily involved in AD by standard methods but little or not at all in PSP. 

Surprisingly, the results were that the transcriptome abnormalities (relative to non-neurological controls) were quite similar in all four types of tissue – AD temporal cortex, PSP temporal cortex, AD cerebellar cortex and PSP cerebellar cortex.  In their words, “The DEG [differentially expressed gene] changes between AD and PSP in two regions of the brain demonstrate a striking conservation [consistency] of transcriptomic changes across these different neurodegenerative diseases.”

Because the degree of traditionally measurable cell damage differed markedly across those four sets of samples, they infer that the changes are “upstream,” meaning at an early step in the disease process, rather than “downstream,” in reaction to damage.  That would mean that even in the early stages of AD and PSP, the disease process is already at work in areas that have not started to show physical signs of damage as assessed by microscope, MRI or PET scan.

What were the networks most affected by the transcriptomic changes?  In the authors’ words: “Up-regulated in both AD and PSP were gene networks serving chromatin modification, gene expression, chromosome organization and metabolism of nucleotides. In the cerebellum the shared upregulated genes link to biological processes relating to RNA and RNA transcription, cell-cell junctions, and heart, kidney, gland, and circulatory system development. Shared down-regulated genes in AD and PSP are associated with gene ontology cell compartment terms related to mitochondrial and ribosomal functions in both the temporal cortex and the cerebellum.”  

The paper’s first author is Xue Wang, PhD, a bioinformatician at Mayo.  The last two authors, sharing credit as senior authors, are Todd Golde, MD PhD of the University of Florida and Nilufer Ertekin-Taner, MD PhD.  I emailed Dr. Taner for her take on the results.  She replied in part, “These findings can be leveraged to develop multifaceted therapies and biomarkers that address these common, complex and ubiquitous molecular alterations in neurodegenerative diseases.”  I’d agree.

So, this unexpected discovery suggests that it may prove fruitless to look for causes of specific neurodegenerative diseases in their gene expression profiles.  Abnormal gene expression may not be the true origin of the disease, but only the cell’s reaction – not to downstream physical damage visible with standard tools, but to some other, far more upstream causation.  Yet, interrupting that reaction at the level of its mRNA might be the key to halting the progression of multiple, of not all, neurodegenerative diseases.  Adding to the appeal of that approach is that the treatment targets are available at a very early stage of the disease process.

Testing that suggestion will have to start with analyzing more than just AD and PSP, and I’m guessing that this effort is already in progress thanks to the excellent collection at the Mayo Brain Bank.  I’ll keep you informed.

A shock to the system

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Researchers at McGill University in Montreal have reported improvement in gait speed in a woman with PSP using transcranial direct current stimulation (tDCS). 

The research findings that I pass along here are generally of high scientific quality.  This one is only a single case report and was published only as a letter to the editor, which typically meets a lower standard in the peer-review process.  But it’s in a good journal and from a well-reputed group with a long record of accomplishment in a closely related field.  Plus, it’s about a low-risk potential treatment of PSP — a disease without much other treatment.  So – good enough for me.

The paper’s first author is Carlos Roncero, MD, PhD, a psychiatrist and psychologist and the senior (i.e., last-named) author is Howard Chertkow, MD.  Both McGill professors have long and distinguished research records.  Dr. Chertkow has worked extensively on tDCS for Alzheimer’s disease and is perhaps most famous for having developed, along with two colleagues, the Montreal Cognitive Assessment (MoCA), a quick test of general cognition that works very well in PSP and other frontal lobe conditions and is used world-wide. 

There has been research before in both tDCS and in transcranial magnetic stimulation for movement disorders, including a bit in PSP.  But the previous work has used arcane physiological variables or speech as their outcome measures rather than gait or balance.

The methods

The procedure consists of passing a weak electric current through the brain, in this case from two electrically negative electrodes (“anodes”) on the skin, one over each deltoid muscle (at the shoulder), to a single positive electrode (“cathode”) atop the center of the head, where the left and right “primary motor cortices” nearly touch.  Nothing pierced the skin – these were just wires ending in 5 x 7-cm (2 x 3- inch) patches held by adhesive. Each deltoid received 2 milliamps of current over 20 minutes per day for 4 consecutive days per week for 3 weeks.  The patient’s gait was tested during the fourth stimulation of the third week and then monthly for 5 months after the stimulation sessions had ended.  As a placebo control, before the first week of stimulation, they gave the patient a week of sham stimulation, with the apparatus in place but the switch off, and considered the gait result at that point to be her baseline.  The nature of the gait test was the time required to walk 24 meters (26 yards) using the same walker that the patient was using at home.  Three clinicians flanked her to prevent falls but did not touch her or the walker.

Here are the results:

Note that the “interval time” on the vertical axis is the time to cover 3 meters, calculated by timing the patient for the 24 meters and dividing by 8.  The average healthy woman of that age (61) walking at maximum speed covers 3 meters in about 1.6 seconds and walking comfortably in 2.3 seconds. (I calculated those times from the reference data in this publication.)  With only sham stimulation, the patient’s time for 3 meters was 11.92 seconds.  It sped up to 9.46 seconds by the end of the third week. The time improved further a month later and further still a month after that, to 7.47 seconds.  After another month, it started to return to baseline and returned a bit further a month later, but then stabilized at about 9.8 seconds for 3 weeks.  So they resumed the stimulation and the next week brought improvement to 8.72 seconds. 

There are some methodological issues. 

Unfortunately, the gait was not tested pre-sham and the patient was not asked if she knew that she had received a sham treatment and when it was given.  If the real stimulation had produced a bit of an electrical sensation in her skin, that could have had a placebo effect with a resulting false-positive result.

Secondly, we don’t know how much, if at all, the speed would have improved beyond that 8.72 seconds if after 5 months had they had given the treatment for the same 3 weeks as the first time.  We also don’t know if this degree of improvement made a difference to the patient’s activities of daily living; nor if it was accompanied by an increased risk of falling not observable over the short time sample of the tests. 

Another caveat is that the gait was assessed using a simple timing of gait speed with a walker rather than with an automated gait analysis system.  Such devices are available commercially and typically have the patient placed in a harness to prevent falls and monitor dozens of variables transduced through electronic contacts embedded in a long walking mat. 

The clinicians with the patient during her walking tests were aware of whether she was receiving sham or real treatment and could have unconsciously influenced her performance. 

Bottom line

In summary, this harmless electrical stimulation procedure may eventually prove to give moderate improvement in gait speed in people with PSP, with long-term retention of benefit.  This result could serve as justification for a grant to study the issue in a larger group of patients and using more rigorous procedures and an assessment of improvement in the patients’ activities of daily living.

The methodologic informalities I’ve complained about are standard in exploratory research, which I’m sure is why this prestigious journal’s editor accepted the manuscript.  This is a good example of how science doesn’t just come up with new knowledge, “eureka!”-style.  The process is full of fits and starts, blind alleys, disagreements, human error, and lots of sweat, with one piece providing a toehold for the next until something useful emerges and is confirmed by others.   

OK, so maybe we do have a marker.

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You may recall a post from last week lamenting the state of diagnostic markers for PSP.  But now I’m happy to report that things are starting to look up. 

A paper in the current issue of Movement Disorders is from a group at Fudan University in Shanghai led by Dr. Ling Li.  Two of the 17 authors work at Taiwan-based Aprinoia Therapeutics.  Last on the author list is the “Progressive Supranuclear Palsy Neuroimage Initiative” (not to be confused with the 4-R Tau Neuroimaging Initiative based at UCSF under Adam Boxer).  I don’t know if the PSPNI is an academically-based research group or a consortium created by Aprinoia.  I’ll try to find out.  In any case, Aprinoia is developing a PET tau ligand called [18F]-APN-1607, formerly known as [18F]-PM-PBB3. 

The new report in the current issue of Movement Disorders is from group from Fudan University in Shanghai led by Dr. Ling Li.  Two of the 17 authors work at Taiwan-based Aprinoia Therapeutics.  Last on the list of authors is the “Progressive Supranuclear Palsy Neuroimage Initiative” (not to be confused with the 4-R Tau Neuroimaging Initiative based at UCSF under Adam Boxer).  I don’t know if the PSPNI is an academically-based research group or a consortium created by Aprinoia.  I’ll try to find out.  In any case, Aprinoia is developing a PET tau ligand called [18F]-APN-1607, formerly known as [18F]-PM-PBB3. 

First, a little background:

What’s a “PET ligand”? What’s “PET”? Positron emission tomography is a way of mapping the locations of a specific compound (called the “target”, typically a protein of some sort) in the body. First, a compound (the “ligand”) that can bind to the target, and hopefully only to that target, is formulated, and that’s the hard part scientifically. Then the ligand is attached to an atom that emits radiation, specifically positrons, for a time that’s short enough to avoid poisoning the patient or the environment. The most common positron-emitting atom is fluorine-18, but carbon-11 is another common one you’ll see. The resulting compound is injected intravenously into the patient. In about an hour or so, the ligand has bound to its target molecule. After a positron has traveled about a millimeter, it has lost enough energy that when it next hits an electron, the two annihilate each other, emitting two photons (in this case also called gamma particles) in opposite directions. The patient is precisely positioned next to a type of camera that can detect these, and when it detects two photons at exactly the same time, it calculates their common point of origin and puts a dot on its software map accordingly. The result is a series of 2-dimensional slices showing the locations of the positron emitter with its ligand. PET images are initially just shades of gray but for ease of eyeball interpretation are typically displayed in an arbitrarily chosen array of colors, with the “cool” blue colors signifying low ligand uptake and “hot” reds the highest uptake.

Although the FDA approved Tauvid (flortaucipir; [18F]-AV-1451; [18F]T807) in May 2020 as a tau-directed PET ligand for Alzheimer’s, neither that compound nor several other candidates have proven adequate in PSP.  The main reasons have been that the “tau burden” in PSP is only 1% of that in AD, which makes the PET signal insufficiently distinguishable from the normal brain’s background.  Also, PET in general has a much lower spatial resolution than MRI or even CT, so the small size of PSP’s specific areas of involvement makes it hard for PET to distinguish PSP from other disorders.  Another issue has been non-specific binding. That is, some candidate tau PET ligands bind less to tau than to other compounds that tend to occur in the same set of brain cells but may not be affected much in PSP.  A good example has been [18F-THK-5351, which distinguishes PSP from healthy people, but was found to bind mostly to monoamine oxidase B, an enzyme important in dopamine metabolism.

Another ligand, [18F]-PI-2620, has avoided that pitfall and distinguishes PSP from healthy controls.  It has not yet been shown to distinguish PSP from other atypical parkinsonisms, though adequate studies of that question have not been published.  Nor has [18F]-PI-2620 been tested in patients with early PSP, where there is greatest need for a diagnostic marker – the average PSPRS score of the patients in the one published diagnostic study was 38 (0 normal, 100 worst possible), by which time PSP is usually easily diagnosable at the “bedside.” (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341407/)  Nor has that ligand been tested for its ability to distinguish PSP-RS from other subtypes or to track disease progression over time.

Another ligand,[18F]-PI-2620, has avoided that pitfall and distinguishes PSP from healthy controls.  But it has not yet been shown to distinguish PSP from other atypical parkinsonisms, though adequate studies of that question have not been published.  Nor has [18F]-PI-2620 been tested in patients with early PSP, where there is greatest need for a diagnostic marker – the average PSPRS score of the patients in the one published diagnostic study was 38 (0 normal, 100 worst possible), by which time PSP is usually easily diagnosable at the “bedside.” (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341407/)  Nor has that ligand been tested for its ability to distingish PSP-RS from other subtypes or to track disease progression over time.

This week’s development

The news flash is that [18F]-APN-1607, has leapt ahead of [18F]-PI-2620, at least for now.  (Not that we shouldn’t have multiple tau PET ligands for PSP with slightly different properties for different clinical situations – that would be great!)  The paper of Li et al included 20 patients with PSP (a lot for an early-phase PET study), of whom 16 had probable PSP-Richardson syndrome, 2 had PSP-parkinsonism, 1 had PSP-progressive gait freezing and 1 had “suggestive of” PSP.  Their average PSP Rating Scale score was 31.6, which is toward the milder end of the range typical of PSP drug trials and milder than the patients in the l[18F]-PI-2620 trial.  There were also 7 with MSA-parkinsonism, 10 with Parkinson’s disease (both of which are alpha-synucleinopathies, not tauopathies) and 13 healthy controls.  The results were corrected for any effects of age, sex, or disease duration and for multiple comparisons.   

The study found that [18F]-APN-1607 PET shows major differences between PSP and healthy controls in 12 brain regions known from autopsy studies to be affected most in PSP. The same could be said for the comparisons of PSP with Parkinson’s or MSA-P, although when only the putamen (part of the basal ganglia) was considered, 4 of the 7 patients with MSA-P had as much binding as those with PSP.  So the authors combined the measurements from the substantia nigra (part of the midbrain, which is part of the brainstem) with those of the putamen, achieving much better separation.  Still it was far from perfect: The standard measure of diagnostic accuracy at an individual patient level, as opposed to merely comparing two groups’ average measurements, is the area under the receiver operating curve (AUC).  That statistic, where perfect is 1.0 and useless is 0.5, takes into account both sensitivity and specificity.  The AUC based on [18F]-PI-2620 uptake in putamen and midbrain for PSP vs the synucleinopathies was 0.811 and for PSP vs. controls, 0.909.  Good but not great.

When they homed in on the subthalamic nucleus, a tiny area that may be where PSP starts in the brain, the AUC was an excellent 0.935 (0.975 for MSA-P and 0.908 for PD).  But that nucleus is so small relative to the spatial resolution of PET that it could be a problem to train large numbers of radiologists and technicians to measure it in the real world using real-world hardware and software.

Li L, Liu F-T, Li M, et al. Movement Disorders 36: 2314-2323, 2021.

In the figure above, the first and fifth columns are the MRI images used as templates on which the PET images (the colored areas in the other columns) are superimposed. The group of images on the left are axial images through the planes of (from left to right) the pons, midbrain and putamen. On the right are sagittal images through planes a bit left of midline, midline and a bit right of midline. Each row is one patient with the condition listed at the far left. (HC means healthy control.) Note that all three subtypes of PSP show strong uptake of the tracer in the putamen and midbrain and none of the other patients shows this combination. The brain area with the greatest difference between PSP and non-PSP, the subthalamic nucleus, is too small to appear to the naked eye as a clear and separate dot in these images.

Flies in the ointment

A major pitfall for [18F]-PI-2620 is its sensitivity to light, which renders it inactive.  A solution to this problem would require not only opaque containers, but also opaque IV tubing.  This can be achieved by wrapping transparent tubing in foil, a standard procedure in hospitals for other photosensitive drugs, but one with obvious drawbacks.

The study of Ling et al did show, for several brain regions, a weak correlation of PSPRS score with [18F]-PI-2620 uptake.  The association was best for the raphe nuclei, an area of the pons (in the brainstem) with widespread connections that use serotonin as their neurotransmitter and are most closely associated with control of sleep.  Weaker, but still statistically significant associations were found also for 5 other areas.  Another selling point for [18F]-PI-2620 is that the PET signal did not correlate with the subject’s age, suggesting that the uptake is related to the severity of the illness and not some effect of aging in the context of illness. However, the duration of illness did not correlate with [18F]-PI-2620 uptake, suggesting that this technique might not be able to document PSP progression or its slowing in response to treatment in a drug trial.

Another issue left untouched by the new publication is whether [18F]-PI-2620 can distinguish PSP from CBD.  That would require subjecting patients with corticobasal syndrome (CBS) to amyloid scanning to rule out Alzheimer’s disease as the cause of their CBS, leaving a tauopathy as the most likely, but not the only, explanation.  Nor were non-Richardson PSP subtypes evaluated, other than in those 2 patients with PSP-P. 

A possible flaw in the methodology is the relatively slow progression of disability in this group of patients (on average, 0.70 PSPRS points per month, compared with about 0.92 in other studies), suggesting some sort of atypicality (or a difference of definitions of the date of onset).  Another is that the PET measurements were obtained at one point in time, which may not have been the best point given the rate of brain uptake and metabolic breakdown of the [18F]-PI-2620.  Using a rate of uptake over time rather than an absolute maximum would have been preferable and is the current state of the art.

Ling et al emphasize that their study is only the beginning of the clinical evaluation of [18F]-PI-2620 in PSP.  Future studies should include larger numbers of patients, more non-Richardson types, CBD, and a repeat scan in each patient after 6 months or more in order to assess the ability of the technique to document disease progression in individuals.

But it’s progress!