07 Dec 2017

To attend the 10th Clinical Trials on Alzheimer’s Disease conference was to witness a field at large grapple with the realization that its focus is in the midst of swinging downward from the visible tip of the iceberg that is Alzheimer’s toward its underwater bulk. Gathered in Boston November 1 to 4, trialists were training their eyes squarely on the 15 years of pathogenic buildup that lead to the roughly eight years of symptomatic disease, which scientists increasingly refer to as brain “organ failure” or “end-stage.”

To be sure, CTAD featured trial data on both amyloid- and non-amyloid drugs, as it does every year, and some of those trials were in mild-to-moderate disease (e.g. see Part 6, Part 8, Part 12 of this series). But the field’s main thrust clearly was on how to apply a new understanding of the pre-dementia stages of AD toward running better therapeutic trials.

“The great advance over the past 10 years since CTAD began is that we now know that AD really is a continuum,” said Reisa Sperling of Harvard Medical School in Boston. “It begins well before what we recognize clinically as dementia and even before the stage we recognize as prodromal. So the question has become: How can we treat the presymptomatic stage? This may be our best opportunity to bend the curve toward normal aging.”

Change would come not a day too soon. The abysmal success rate of the past decade’s clinical trials has been publicized in overly simple terms, said Rachelle Doody, Roche/Genentech, Basel, Switzerland. A public perception of failure clings to Alzheimer’s trials. It must change to one of learning and hope in order to help rally the thousands of volunteers, and motivate site staff, for the massive prevention initiatives that are gearing up around the world (see Part 13 of this series).

After years of debate about causes and clinical groupings, the field’s pulse now is felt most strongly in efforts to identify, engage, and characterize asymptomatic, at-risk participants (see Part 5 of this series). Innovation focuses on ways to tighten up variability, and to capture richer data sets when measuring a person’s subtle cognitive slide toward dementia, both as disease takes hold and in response to investigational drugs (see Part 4 of this series). Clinically certified CSF tests, as well as up-and-coming research-grade blood tests, are energizing international efforts to bring an early diagnosis into routine clinical care and to become more efficient at screening large populations for suitable trial participants (see Part 3 of this series). The field’s collective shift toward treating earlier stages of AD requires change at every step of the clinical trial endeavor, from cohort-building to outcome measures and statistical methods. Advances on display at this year’s CTAD splashed across all these fronts.

Measuring Early Decline
For starters, consider this question: Is it possible to track early cognitive decline? Yes, said Sperling, citing data from the Harvard Aging Brain Study as an example. As shown in previous observational cohorts of cognitively normal aging people, HABS participants with brain amyloid deposition do decline in subtle ways, and this can be measured with the Preclinical Alzheimer Cognitive Composite, aka PACC, a new battery of composite tests. In contrast, HABS participants without brain amyloid get better on the PACC as they retake the tests on subsequent visits. This divergence between loss and learning shows up on each component of the PACC, and it grows over time, Sperling said.

Next, is it possible to measure preclinical progression with biomarkers? Yes again, said Sperling. The model is that preclinical AD represents a confluence of cortical amyloid deposition and tau pathology expanding beyond its age-related confines in the medial temporal lobe into the cortex. This model is being tested by multimodal PET studies that track both amyloid and tau over time, and it appears to hold up. “Preclinical AD is amyloid plus tau spreading into cortex at Braak stages III to IV,” Sperling told the CTAD audience.

Do cognition and pathology relate to each other at this stage? Once again, the answer is yes. Even within the narrow cognitive range of HABS participants, those with the most brain amyloid and the most tau score lowest on the PACC. “In people with amyloid, tau drives memory decline. So if you have a lot of amyloid and a lot of tau, you will not stay normal for long,” Sperling said.

Narrow as it is initially, this gap soon widens. At CTAD, Bernard Hanseeuw of Massachusetts General Hospital, Boston, told of a man who was clinically normal at baseline despite having cortical amyloid plus tau in his entorhinal cortex. Eighteen months later, tau had spread but his MMSE, free recall, and PACC held steady; alas, another year later, tau had invaded the inferior temporal cortex on both sides and his PACC turned abnormal. This pattern holds true as HABS collects longitudinal measurements, Hanseeuw said. To date, serial results on cognition, amyloid, and tau are available for 60 HABS participants. The key finding is that an increase in tau PET in the temporal cortex better predicts decline in cognition than do amyloid or even baseline tau (for details, see Part 2 of this series). “Tau PET is a promising marker for monitoring disease progression and drug efficacy,” Hanseeuw said.

This is more than one enthusiast’s opinion. After a slow start, and problems with some initial investigational tracers, drug developers across the globe are now closely watching validation studies of newer tracers and starting to use them in their trials. “We all in the field see this. Tau PET will be an outcome measure, together with more sensitive cognitive composites. Amyloid is better as an inclusion criterion,” Marc Cantillon, who is advancing an anti-Aβ oligomer antibody into Phase 2 for the Japanese company Kyowa Kirin, told Alzforum (see Part 10 of this series).

Talks throughout CTAD strengthened the perception that tau PET matches cognition and may pack a punch in drug trials. Sergey Shcherbinin, Eli Lilly and Company in Indianapolis, showed an intriguing parallel between tau and cognition when he presented his refinement of an existing approach to derive continuous, stereotypical biomarker staging diagrams from short-term serial data collected in observational study cohorts (e.g., Villain et al., 2012; Villemagne et al., 2013; Jack et al., 2013). Statisticians are honing methods to transform data on the relationship between a given biomarker’s baseline level and its annual rate of change—typically garnered in three- to seven-year stretches of observation in various cohort studies—into sweeping curves that depict the entire 20-year pathogenic process. Ideally, the curves in such an improved, data-driven staging model should incorporate the relationship between individual biomarkers, Shcherbinin said at CTAD.

To that end, Shcherbinin tried his method on all ADNI data available as of February 2017. His way of deriving a trajectory from baseline and rate-of-change data yielded three different curve shapes for the five markers measured. Florbetapir PET assumed a flat sigmoid shape; FDG PET and hippocampal volume both assumed roughly linear shapes, reflecting constant rates of change. However, in line with Hanseeuw’s data, the curves for two markers assumed a parallel, exponential shape marked by accelerated change with higher baseline levels of abnormality. They were cognition and tau PET.

In toto, a picture is emerging of an exponential increase of tau, followed by cognitive decline, in the presence of amyloid. To many scientists, this strengthens the view that once amyloid reaches its plateau, the disease process becomes independent of amyloid.

Targeting Early Decline in Therapeutic Trials
“How can we use this information to help us test the right target with the right drug at the right stage?” Sperling asked. CTAD featured updates on some of the secondary prevention trials that are already underway and additional trials on the drawing board. As currently designed, AD prevention trials can last up to a decade from planning to data. To incorporate research on drugs and biomarker staging that is newly coming out during those years, scientists adjust ongoing trials as regulators allow. For example, after solanezumab flopped in Phase 3 for mild AD, the A4 solanezumab prevention trial in people who are amyloid-positive but cognitively normal quadrupled the dose to 1.6 grams of solanezumab infusion every month. A4 is also lengthening the treatment period to five years in hopes that these changes will reveal what is expected to be a small treatment benefit.

Ditto for the API prevention trial of crenezumab in presenilin-1 E280A mutation carriers in Medellin, Colombia, and for the DIAN-TU prevention trial of gantenerumab in autosomal-dominant AD mutation carriers. Both studies have increased the dose midway through, as have the prodromal and mild AD trials on these antibodies in late-onset AD (see Part 7 in this series).

Incidentally, these dose increases jibe with the newest results on the anti-Aβ antibody aducanumab. At CTAD, Biogen’s Samantha Budd showed 36-month treatment data from the ongoing long-term extension of the aducanumab Phase 1b PRIME trial of people with mild AD. In people who are receiving the highest dose, 10 mg/kg, brain amyloid deposition had dropped below SUVR 1.1, the preset threshold of positivity, by 80 weeks, and stayed this low at 166 weeks. This does not mean plaques are completely gone, Budd said in response to a question, but rather, that their overall burden has dropped below a brain-wide cutoff.

To mitigate aducanumab’s ARIA side effect, Biogen is evaluating a titration scheme that gradually approaches an effective dose. At CTAD, Philipp von Rosenstiel of Biogen showed long-term-extension data for this group of 18 participants. After 24 months, the titration group had about the same amount of amyloid reduction as the 6 mg/kg fixed dose group, and comparable safety. Biogen uses titration in its ongoing Phase 3 program of aducanumab in mild AD.

In toto, both prevention and symptomatic trials of the major antibodies—aducanumab, gantenerumab, crenezumab, solanezumab—are pushing in the same direction of giving high doses for long periods of time.

Further adapting to emerging science, prevention trials have started to add tau PET. A4 added flortaucipir in 2016 and has scanned 381 participants so far. Baseline results mirror Hanseeuw’s finding in the HABS natural history cohort, in that half of these cognitively normal people with amyloid already have cortical tau in their inferior temporal lobes, posterior cingulate, and precuneus. Once again, tau was bad news even in this ostensibly normal phase. A4 tightly limited cognitive inclusion criteria, such that participants had to be normal on MMSE, within one standard deviation on other tests, and could not be supernormal. “Even within this narrow cognitive band, people with highest amyloid have the most tau, and people with the most tau have the lowest memory scores. This was striking to me,” Sperling said. Given this distribution, some scientists speculated that perhaps the less-advanced people within this A4 cohort may still derive a benefit from an antibody that reduces monomeric Aβ, whereas people whose tau is spreading may not, because their disease has become independent of amyloid.

Sperling is not waiting for the answer. “When we submitted the A4 grant five years ago, prevention trials were considered fantasy. Now we know they are feasible, and we are already learning screening data in cohorts who are at risk genetically or by biomarkers. But we cannot wait for results from current trials; we must start additional trials with multiple mechanisms now,” Sperling said. To that end, the A5 trial, aka EARLY, is evaluating Janssen’s BACE-1 inhibitor JNJ-54861911 in a slightly younger population starting at age 60 (instead of A4’s 65), who have amyloid accumulation either by CSF or PET. Fourteen sites are currently enrolling. The Novartis/Banner Generation trials of the BACE inhibitor CNP520 and the active Aβ immunotherapy CAD106 are also enrolling cognitively normal people starting at age 60 who are at genetic or biomarker risk of developing Alzheimer’s dementia.

Alas, ultimately, even age 60 with established amyloid deposition represents a later stage in the long pathogenic process than when Sperling wants to deploy anti-amyloid drugs. Therefore, the next trial, A3, or Ante-Amyloid Prevention of AD, is going to search for people aged 50 to 75 who are at high risk of accumulating amyloid and developing the subsequent biomarker changes predicted on AD staging diagrams. Unlike A4 and EARLY, which measure success on the PACC, this four-year trial will use biomarkers as primary outcomes and cognition only as an exploratory outcome. Alternatively, A3 could pair up with a sister trial of the same drug in a later-stage preclinical population in whom cognitive change is more robustly measurable within the timeframe of a trial, Sperling said. A3 is NIA-funded as part of a public-private partnership, and finalizing its choice of drug now. Who could enter A3? For one, people who tried to join A4 or EARLY but fell below the amyloid cutoff. At CTAD, Sperling noted that 529 people who failed amyloid scanning in A4 have already joined the observational LEARN study as a springboard for an earlier-stage treatment trial that will accept them. For another, A3 will draw people from the TRC PAD cohort being built by the Global Alzheimer’s Platform, or the EPAD-TRC, a trial-ready cohort being built by the European Prevention of Alzheimer’s Dementia project (Aug 2016 conference news), or other online or local registries.

In the big scheme of things, the A3 study represents a link in the needed chain of trial evidence researchers are building to support their push for drug evaluation into ever-earlier disease stages, until they are able to pull off primary prevention of amyloid buildup in middle-aged people. The DIAN-TU is already working on this for people who carry autosomal-dominant mutations (Aug 2017 conference news); A3 is a necessary step toward primary prevention of LOAD. “We are moving toward the left on the staging diagrams,” said Bruno Dubois from University Salpêtrière Hospital in Paris.

How to Fill Prevention Trials?
The advent of prevention trials and their prodigious recruitment needs are spurring attempts at speeding things up. Consider the A4 trial. It started enrolling in early 2014. By November 2017, 67 A4 sites were active in North America, Australia, and Japan. The good news is that A4 will slightly exceed its target by the time recruitment closes at the end of 2017; however, to find these 1,160 participants, sites had to screen nearly 7,000 people, 4,480 of them with an amyloid scan. Of those, only 30 percent were eligible for A4, Sperling reported at CTAD.

Several years to fill a single early stage trial simply does not seem acceptable any more, and experiments to accelerate recruitment are happening throughout the field. At CTAD, Chris Rowe of Austin Health in Melbourne, Australia, presented an example targeted at prodromal-stage trials. “Our new project addresses the problem that many people are being diagnosed clinically every day, but do not get referred to trials,” he told the audience. Rowe’s site has been doing amyloid PET scans since 2004, and amyloid PET is well-known in Australia but not covered by insurance. What if he could give free amyloid scans to referring clinicians across Melbourne for patients who appear eligible for trials and interested in joining one? In this scheme, a trial sponsor pays for the scans done at Rowe’s center. It is a win for all sides, Rowe said, because the sponsor gets prescreened candidates and reduces the trial’s screen failure rate; the clinician can offer a better diagnosis and some hope when telling his or her patients they have early AD; and the patient gets tangible options for fighting the disease by being pointed toward open clinical trials.

AstraZeneca funded the project, and Rowe’s center fielded referral candidates for scanning who fit the inclusion criteria of AstraZeneca/Lilly’s AMARANTH Phase 3 trial of the BACE inhibitor lanabecestat in early AD. However, referring clinicians were not bound to recommend only this trial to their patients once the scan result was in.

Patients referred from across Melbourne, a city of 4 million, were prescreened by phone and then in person at the city’s Florey Institute of Neuroscience and Mental Health. Over the past 18 months, 64 clinicians referred 342 patients. Of those, 108 failed the telephone screen and 82 failed the on-site screen. Of the 150 who got a PET scan, 115 were positive for amyloid plaques, Rowe said. Of those, the Amaranth trial accepted 41.

Why did half still not get in after that much prescreening? Fourteen people declined when they saw how complex the trial was. Ten had deteriorated, 13 had medical reasons or were on disallowed medications. “I am concerned by these exclusions,” Rowe told the audience. Three more people who had positive NAV4694 scans were negative on a subsequent florbetapir scan done as part of Amaranth. “This is not surprising because florbetapir is less sensitive than NAV4694,” Rowe said (May 2010 news). 

An ongoing extension of the program referred 27 additional people to Amaranth. Of the original 115 with positive scans, 32 checked out trials other than Amaranth and 26 of those enrolled. Overall, the program dramatically exceeded the recruitment targets of all the Melbourne AD trial sites, Rowe said. The sponsor’s cost per enrolled person was US$12,000. Importantly, every newly diagnosed patient took up the offer to enter a drug trial. “When people see their scan and hear a diagnosis, they really want to do something about it,” Rowe said.

“This is practical and extremely helpful,” said Steve Salloway of Butler Hospital in Providence, Rhode Island. It could be replicated at other PET centers that have a strong referral base among AD clinicians.

To bring down recruiting time, clinicians want quick tests to tip them off about the likely presence of brain amyloid in a given person; to rein in cost, they specifically want prescreening tools that help them decide who to refer for a PET scan. Besides fluid-based Aβ tests, there may soon be other ways of going about it. John Hardy of University College, London, started his CTAD keynote by saying, “As geneticists, we have not yet done anything terribly useful for patients.” This may soon change, however, which is why Hardy addressed an audience of trialists. He believes that polygenic risk scores, aka PRS, have become good enough to reduce the screen failure rate of prodromal and prevention trials.

In the current era of GWAS and large-scale sequencing, neurogenetics has reached a point where it can apply to clinical use the collective set of variants gathered for the nearly 40 genes that are universally accepted to influence AD risk. The time is right because most genetic variance has been captured. “We know that not all monozygotic twins are concordant for AD, so we will never be able to use genetics alone to predict absolutely who will get AD,” Hardy said. But polygenic risk scores derived from GWAS variants come close, predicting up to 90 percent of genetic risk, much as twin studies do (Escott-Price, Shoai, et al., 2017; Escott-Price, Myers et al., 2017). Indeed, at CTAD, UCL’s Maryam Shoai presented a study testing a new polygenic risk score derived from a training set of 1,700 neuropathologically confirmed cases. This PRS predicted with 90 percent sensitivity who was amyloid-positive among a second set of 600 ADNI samples, Shoai showed. Also at CTAD, Chin Hong Tan in Rahul Desikan’s group at University of California, San Francisco, presented similar data on a genetic tool they call polygenic hazard scores.

Such a test could serve as an upstream check of who should go on to have a PET scan as part of trial screening. It could also become part of the characterization of at-risk participants in the trial-ready cohorts being built in Europe, North America, and Australia. “You can use this now to cut down on PET scans and lumbar punctures,” Hardy told the assembled trialists in Boston.

Perhaps more provocatively, polygenic risk scoring can also unmask misclassification in general clinical samples, Hardy told the audience. For example, applying PRS to the samples that formed the basis of the large IGAP GWAS showed that 10 percent of its E4 carriers and 30 percent of noncarriers were classified as healthy controls when their PRS indicated that they were likely amyloid-positive. At age 75, one in five were clinically classified as controls even though their genetics indicated they had brain amyloid deposition, Hardy said.

To Paul Aisen, University of Southern California, the improving AD biomarker staging scheme, combined with tools to capture risk and biomarker status of people in standing trial cohorts, suggests a game plan for the future. “For primary prevention, we will use a BACE inhibitor. I think it will be a cure. For secondary prevention, we will use an antibody and a BACE inhibitor. For prodromal AD, we need a third drug of a different class, probably a tau drug. For mild to moderate AD, I don’t know yet what the combination will be. We need to learn more. But we will succeed,” Aisen told Alzforum.

To this end, scientists at CTAD renewed their call for industry and regulatory scientists to buckle down and start combination trials of two investigational drugs. Word in the hallways had it that some of the companies that have both the necessary Aβ antibodies and BACE inhibitors drugs—Lilly, Roche, and Eisai, for example—are nearing the launch of a first such trial in early 2018, though no one was ready to make an announcement yet.

Meanwhile, a range of single-drug trials are moving forward (see Part 9, Part 11 of this series), while others closed the book on their candidate drugs (see Part 12 of this series).—Gabrielle Strobel

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References

News Citations

1. Verubecestat Negative Trial Data: What Does it Mean for BACE Inhibition? 12 Dec 2017
2. Pimavanserin Trial Raises Hope for Treating Dementia-Related Psychosis 12 Dec 2017
3. At Least We Know These Don’t Work: Negative Trials at CTAD 15 Dec 2017
4. No Negativity, Please. Clinical Trial Leader Urges Focus on Learning, Progress 18 Dec 2017
5. Cognitive Testing Is Getting Faster and Better 9 Dec 2017
6. Automated CSF Tests: Check. Blood Tests: In the Works 8 Dec 2017
7. At CTAD, Tau PET Emerges as Favored Outcome Biomarker for Trials 8 Dec 2017
8. Elusive or Not, Aβ Oligomers Are in BioPharma Crosshairs 13 Dec 2017
9. High-Dose Gantenerumab Lowers Plaque Load 13 Dec 2017
10. Access: How to Bring People in ‘From the Wild’? 11 Aug 2016
11. Planning the First Primary Prevention Trial for Alzheimer’s Disease 7 Aug 2017
12. Geneva: The AstraZeneca Ligand—The Fairest of Them All? 10 May 2010
13. Blood, the Secret Sauce? Focus on Plasma Promises AD Treatment 14 Dec 2017
14. In the Running: Trial Results from CTAD Conference 14 Dec 2017

Therapeutics Citations

1. Solanezumab
2. Crenezumab
3. Gantenerumab
4. Lanabecestat

Paper Citations

1. Villain N, Chételat G, Grassiot B, Bourgeat P, Jones G, Ellis KA, Ames D, Martins RN, Eustache F, Salvado O, Masters CL, Rowe CC, Villemagne VL, AIBL Research Group. Regional dynamics of amyloid-β deposition in healthy elderly, mild cognitive impairment and Alzheimer's disease: a voxelwise PiB-PET longitudinal study. Brain. 2012 Jul;135(Pt 7):2126-39. Epub 2012 May 23 PubMed.
2. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, Szoeke C, Macaulay SL, Martins R, Maruff P, Ames D, Rowe CC, Masters CL, Australian Imaging Biomarkers and Lifestyle (AIBL) Research Group. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol. 2013 Apr;12(4):357-67. Epub 2013 Mar 8 PubMed.
3. Jack CR, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue MC, Trojanowski JQ. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013 Feb;12(2):207-16. PubMed.
4. Escott-Price V, Shoai M, Pither R, Williams J, Hardy J. Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease. Neurobiol Aging. 2017 Jan;49:214.e7-214.e11. Epub 2016 Aug 5 PubMed.
5. Escott-Price V, Myers AJ, Huentelman M, Hardy J. Polygenic risk score analysis of pathologically confirmed Alzheimer disease. Ann Neurol. 2017 Aug;82(2):311-314. Epub 2017 Aug 9 PubMed.

Other Citations

1. Part 5

Further Reading

No Available Further Reading