Tag Archives: MCI

Reprinted from the Cornell Chronicle, November 4, 2016.

By Tom Fleischman

Front and side views of two regions of interest for the origins of Alzheimer's disease - the basal forebrain, top, and the entorhinal cortex, bottom.

Alzheimer’s disease is a neurodegenerative disorder for which, despite years of research, there are no effective treatments or cures. However, recent breakthroughs in molecular genetics have shown that the disease may spread, like an infection, across closely connected areas of the brain. These findings underscore the need for research aimed at tracking its spread to the earliest points of origin in the brain, so therapies that target those areas can be developed.

An international collaboration between Nathan Spreng, Cornell assistant professor of human development and the Rebecca Q. and James C. Morgan Sesquicentennial Faculty Fellow in the College of Human Ecology, and Taylor Schmitz of the University of Cambridge’s Cognitive Brain Sciences Unit, sheds light on the basal forebrain region, where the degeneration of neural tissue caused by Alzheimer’s disease appears even before cognitive and behavioral symptoms of the disease emerge.

Their paper, “Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer’s pathology,” is published Nov. 4 in Nature Communications. Data used for their work were obtained from the Alzheimer’s Disease Neuroimaging Initiative database.

The basal forebrain contains very large and densely connected neurons that are particularly vulnerable to the disease. Schmitz and Spreng show that, as Alzheimer’s progresses, degeneration of the basal forebrain predicts subsequent degeneration in temporal lobe areas of the brain involved in memory. This pattern is consistent with other research showing that Alzheimer’s indeed spreads across brain regions over time, but the study challenges a widely held belief that the disease originates in the temporal lobe.

“We’re hoping that this work pushes a bit of a reorganization of the field itself, to reappraise where the disease originates,” Spreng said. “That could open up new avenues for intervention; certainly it would for detection.”

Their report is the product of a two-year study of a large sample of age-matched older adults. Within this sample, one group was cognitively normal, according to standard tests, while others were characterized by different levels of cognitive impairment:

  • Individuals with mild cognitive impairment (MCI) who did not progress to Alzheimer’s disease;
  • MCI individuals who progressed to Alzheimer’s after one year; and
  • Individuals classified as having Alzheimer’s throughout the duration of the study.

Through analysis of high-resolution anatomical magnetic resonance imaging of brain volumes, taken three times over the two-year study period, the researchers were able to determine that individuals with MCI or Alzheimer’s showed greater losses in gray matter volume in both the basal forebrain and temporal lobe, compared with cognitively normal controls. Intriguingly, they showed that over the two-year period, degeneration of neural tissue in the basal forebrain predicted subsequent tissue degeneration in the temporal lobe, but not the other way around.

A sampling of spinal fluid from healthy adults can detect an abnormal level of beta amyloid, indicative of Alzheimer’s, Spreng said. Test results showed that temporal lobes looked the same regardless of amyloid level, but the basal forebrain showed notable degeneration among those seemingly healthy adults with abnormal amyloid levels.

Spreng admits that being able to predict who will get the disease doesn’t mean a lot without a protocol to treat and, ultimately, cure the disease. “And it might induce more anxiety,” he said. But the more knowledge that can be gained now, he said, the better.

“Future molecular genetics work holds strong promise for developing therapeutic strategies to prevent the spread of pathology at stages of Alzheimer’s preceding cognitive decline,” Schmitz said. “Our clarification of an earlier point of Alzheimer’s propagation is therefore of utmost importance for guiding endeavors to combat this devastating disease.”

This work was funded by grants from the National Institutes of Health and the Alzheimer’s Association.

By H. Roger Segelken
Reprinted from Cornell Chronicle, April 29, 2015

Remember HAL, the onboard computer in “2001: A Space Odyssey,” struggling to sing “Daisy, Daisy…” while astronaut Dave disables older and older memory modules until just one shred of HAL’s artificial intelligence remains?

Who could forget … except that’s not how language loss really happens to humans on the verge of Alzheimer’s disease, according to a team of psychologists and linguists with a paradigm-flipping test to predict the disease.

“It is now known that Alzheimer’s disease may develop for years, silently, before appearance of symptoms leading to clinical diagnosis,” explains Cornell’s Barbara Lust. “We’re searching for early signs in the spoken language of individuals, before Alzheimer’s is actually manifest.”

Together with research collaborators at Cornell and three other institutions, Lust published surprising findings in the April journal Brain & Language, “Reversing Ribot: Does regression hold in language of prodromal Alzheimer’s disease?”

Theodule Ribot was the 19th-century French psychologist who proposed a law of regression or reversion - essentially that “structures last formed are the first to degenerate ... the new perishes before the old.” Ribot’s law predicts what is often observed in Alzheimer’s patients, that recent memories may be lost before older memories.

The new study inquired whether there are also changes in language that occur during the prodromal course of Alzheimer’s disease – changes that possibly could be predictors of the disease. Prodromal refers to the period before appearance of initial symptoms and the full development of disease. The stage of prodromal Alzheimer’s, before dementia sets in, is called Mild Cognitive Impairment or MCI.

The researchers asked whether the course of language deterioration in prodromal Alzheimer’s would systematically reverse the course of acquisition of language among children, in accord with Ribot’s prediction.

The study compared earlier research – on the course of language development of complex sentences in children under age 5 – with new research assessing language patterns of MCI adults.

Researchers also tested young adults and healthy aging adults. Adults were asked to imitate sentences with complex structures, including various types of relative clauses, just as the children had.

As hypothesized by the researchers – but contrary to common belief – the linguistic structures children develop first are the ones MCI adult subjects struggle with the most.

For example, individuals with MCI found it more difficult to repeat a sentence like, “The office manager corrected what bothered the summer intern,” often giving responses like “The officer ... uh ... inspected ... and um ... corrected the intern.”

For children, sentences like “Fozzie Bear hugs what Kermit the Frog kisses” were the earliest produced. Whereas sentences like “Scooter grabs the candy which Fozzie Bear eats” were late-developed by children – but easiest for MCI adults.

In MCI, a first-developed structure is being lost first and a last-developed structure is being retained longest – contrary to Ribot’s prediction ... and HAL’s experience.

Next, researchers hope to incorporate linguistic assessments into potential predictive tests for early-stage Alzheimer’s, as they further test their results with additional subjects for verification.

Collaborating with Lust, a professor of human development in the College of Human Ecology, were Cornell senior research associate Charles R. Henderson, Jordan Whitlock ’11, Alex Immerman ’08, Aileen Costigan and James Gair, professor emeritus of linguistics. Collaborators from other institutions were Suzanne Flynn, M.A. ’80, Ph.D. ’83, Massachusetts Institute of Technology; Janet Cohen Sherman, Ph.D. ’83, and Sarah Mancuso, Massachusetts General Hospital; and Zhong Chen, Rochester Institute of Technology.

Research was funded, in part, by Hatch Grants and Federal Formula Funds, as well as grants from the Bronfenbrenner Center for Translational Research, Cornell Institute for Translational Research on Aging, and Cornell’s Institute for the Social Sciences.