Part 4 of a five-part report.
Asking whether autosomal-dominant Alzheimer’s disease is essentially the same disease as sporadic late-onset AD is a sure-fire way to spark debate among researchers. This debate has raged since the 1970s, when Bob Katzman just about equated Auguste Deter’s middle-age affliction to the “senility” that ailed millions of older Americans. “Lumpers” among the scientific community emphasize the abundant similarities in biomarker trajectories and the clinical/cognitive course between the rare and the common forms of AD; “splitters” cite differences ranging from a different starting region of amyloid PET to clinical variations such as spastic paraparesis and epilepsy. And then there is age. Does aging mean LOAD is a heterogeneous syndrome, essentially a collection of many diseases? Or does the aging process contribute separate, age-related co-morbidities to the central pathway of Alzheimer’s disease?
Many scientists maintain that LOAD is heterogeneous, but others disagree. “There is a mythology out there that AD is heterogeneous. I think it is homogeneous, with added variables of aging,” Colin Masters, University of Melbourne, Australia, told an audience at the Alzheimer’s Association International Conference, held July 22-28 in Toronto.
The question is far from academic. As soon as the first drug shows evidence of working in ADAD, regulators will confront the quandary of whether to approve it only for this small subgroup or for all AD patients. “If we find a drug that works in ADAD, will it work in LOAD?” asked Virginia Buckles of Washington University, St Louis.
The literature on the peculiarities of autosomal-dominant AD, or dominantly inherited AD (DIAD) as DIAN researchers call it, comprises small patient series or individual case reports, and it is marked by reporting bias. One ADAD family suffers spastic paraparesis—that makes a paper. The next four do not—that’s unremarkable, hence no paper. However, eight years into the DIAN project, observational data on 465 participants followed in a standardized way make for a comprehensive data set to analyze in search of a more definitive answer. For LOAD, large data sets exist by now, as well, such as those from the Alzheimer's Disease Neuroimaging Initiative (ADNI) or the National Alzheimer’s Coordinating Center (NACC). This DIAD-LOAD comparison aims to build a knowledge base that regulators can consult to support an informed decision, said Randy Bateman of Washington University, St. Louis, who leads the DIAN initiative. It is a multipronged project that will go on for some time, but at the AAIC conference the first glimpses were visible.
Consider postmortem pathology. How do the brains of people who died from either disease compare to each other? Nigel Cairns, who heads the neuropathology core for both DIAN and ADNI, showed the data available so far. Twenty-four DIAN participants or relatives who carried the family mutation have come to autopsy. Unsurprisingly, each of them had a neuropathologic diagnosis of AD; 13 of them also met diagnostic criteria for dementia with Lewy bodies (DLB). Importantly, they had no other discernable pathologies, Cairns said.
From ADNI, 50 cases have come to autopsy. Of those, two never had Alzheimer’s at all. They had argyrophilic grain disease (AGD) plus another age-related tauopathy called PART. Eighteen had pure Alzheimer’s disease with amyloid plaque and neurofibrillary tangle pathology, 22 had AD with DLB. The remaining 22 cases all had AD plus another co-morbidity—either TDP-43, AGD, an age-related tau astrogliopathy called ARTAG, hippocampal sclerosis, or infarcts. At death, the ADNI participants were 30 years older than DIAN participants on average, 81 versus 51. What might be going on? Cairns suspects that with advancing age, other lifestyle or genetic factors come to bear on AD pathogenesis.
Another emerging research trend is that white-matter hyperintensities appear to start early in both ADAD and LOAD. Cairns is now trying to relate the last MRI FLAIR scans taken before death in DIAN and ADNI cases against postmortem signs of white-matter degeneration.
What about during life? Does cognition decline similarly or differently? At AAIC, Buckles showed a comparison of progression rates before and after symptom onset between 129 people in DIAN on the one hand and 853 people in the NACC data set on the other. She was able to compare cognition directly, because DIAN uses some tests from the Unified Data Set (UDS) that were instituted to standardize assessments across the nationwide network of some 30 federally funded Alzheimer’s Disease Centers (ADC), where people throughout the United States seek Alzheimer’s care.
The NACC’s UDS database contains cognitive decline data on more than 33,000 people, but only a subset met the criteria Buckles had set for this comparison. For one, people had to have had neuropathologically confirmed AD in order to be equivalent to the DIAN data set. For another, they had to have been cognitively normal at the time they started being followed at an ADC, so that their whole progression from asymptomatic through dementia could be calculated.
By aligning each person with ADAD or LOAD at their respective point of symptom onset, and then calculating rates of longitudinal change prior to and after that point in time, the researchers were able to sidestep the 30-year age difference of the two groups. “ADAD represents AD without the co-morbidities of aging, hence we compared groups on disease course instead of age,” Buckles said.
Of the 13 cognitive tests in this comparison, progression on 10 was the same between ADAD and LOAD, Buckles said. Three were different: on the Boston naming test and both the Trials A and B tests, LOAD progression rates in the NACC data were steeper. A composite of these three also showed faster decline in LOAD. Then Buckles realized that these are speeded components, and aging is marked by a slowing in thinking and processing information. When Buckles subtracted the three speeded tests, ADAD and LOAD progression slopes both before and after onset became almost identical. This was true not just for progression but also for people’s performance scores at symptom onset: Except for the three speeded components, the scores were highly similar for ADAD and LOAD. “We found the expected age difference on speeded tasks, but without those tasks, ADAD and LOAD declined at the same rate,” Buckles said.
Other researchers praised this talk as “compelling,” and AAIC attendees later mentioned it as standing out in their minds; however, Buckles cautioned that further analyses, particularly of the role of vascular disease and other co-morbidities, still need to be made.
Finally, consider genetic modifiers. For the most part, the field of pinning down variant genes that influence the onset or course of Alzheimer’s disease remains in its infancy; however, one genetic commonality between LOAD and ADAD reportedly comes in the form of the Val66Met variant of the gene for brain-derived neurotrophic factor (BDNF). In the Australian AIBL cohort of LOAD, this common variant has been implicated in accelerating cognitive decline once a person has brain amyloid deposition (Lim et al., 2013; Lim et al., 2014). At AAIC, Yen Ying Lim of the University of Melbourne said that she wanted to see if this was true in other study cohorts, as well, or rather was due to a national quirk she cheerfully called “beer-derived neurotrophic factor.”
Lim was eager to see whether the BDNF Val66Met variant made a difference in DIAD, because these families lack the co-morbidities of aging. She analyzed a sample of 95 presymptomatic DIAN participants who carried the Val66Val variant and 48 with the Val66Met variant. The BDNF Val/Met carriers had the same amyloid load as Val66Val carriers, but their episodic memory performance, glucose metabolism, and tau pathology were more abnormal. “BDNF does not act on amyloid deposition; rather, it acts on the brain’s ability to withstand the downstream effects of amyloid. It takes homozygous Val/Val carriers longer before the full clinical syndrome of disease presents itself. This is the same in LOAD and ADAD,” Lim said. In both forms of AD, BDNF may exert its effect via tau.—Gabrielle Strobel
- Lim YY, Villemagne VL, Laws SM, Ames D, Pietrzak RH, Ellis KA, Harrington KD, Bourgeat P, Salvado O, Darby D, Snyder PJ, Bush AI, Martins RN, Masters CL, Rowe CC, Nathan PJ, Maruff P, . BDNF Val66Met, Aβ amyloid, and cognitive decline in preclinical Alzheimer's disease. Neurobiol Aging. 2013 Nov;34(11):2457-64. PubMed.
- Lim YY, Villemagne VL, Laws SM, Ames D, Pietrzak RH, Ellis KA, Harrington K, Bourgeat P, Bush AI, Martins RN, Masters CL, Rowe CC, Maruff P, AIBL Research Group. Effect of BDNF Val66Met on memory decline and hippocampal atrophy in prodromal Alzheimer's disease: a preliminary study. PLoS One. 2014;9(1):e86498. Epub 2014 Jan 27 PubMed.
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