White matter tract correlations with spoken language in cerebrovascular disease

Assessment of spoken language is a promising marker for cognitive impairment in individuals with cerebrovascular disease. However, the underlying neurological basis for spoken language beyond single words and sentences remains poorly defined in this cohort, particularly with respect to white matter. This study aimed to examine and compare white matter hyperintensity volumes and diffusion tensor metrics in normal-appearing white matter (NAWM) as potential correlates of spoken language performance. Baseline imaging and spoken language data were obtained from the cerebrovascular disease cohort of the Ontario Neurodegenerative Disease Research Initiative (<i>n</i> = 127; age: 55-85 years). Most participants had subclinical or very mild strokes, with very little to no aphasia symptoms. Spoken language samples were analysed to compute 10 different measures related to syntax, productivity, lexical diversity, fluency, and information content. Structural and diffusion MRI data were analysed to segment white matter hyperintensities and tracts. Normalized white matter hyperintensity volume, as well as average fractional anisotropy and mean diffusivity in the normal-appearing portion of eight white matter tracts, were correlated with the 10 spoken language measures using canonical correlation analyses. White matter and spoken language variate scores for individual participants then were correlated separately in male (<i>n</i> = 86) and female (<i>n</i> = 41) participants to probe potential sex differences. Spoken language performance was significantly associated with the fractional anisotropy (<i>r<sub>c</sub></i> = 0.51, <i>P</i> <i>=</i> 0.041) and mean diffusivity (<i>r<sub>c</sub></i> = 0.56, <i>P</i> <i>=</i> 0.011) of NAWM, particularly in the left superior longitudinal fasciculus, but not with white matter hyperintensity volumes (<i>r<sub>c</sub></i> = 0.41, <i>P</i> <i>=</i> 0.80) in the same tracts. Measures related to syntax, fluency, and information content loaded most strongly in the spoken language variate. No significant sex differences were found in NAWM microstructure, and female and male participants exhibited similarly strong associations between spoken language and NAWM microstructure (fractional anisotropy: <i>z</i> = 1.44, <i>P</i> = 0.15; mean diffusivity: <i>z</i> = 1.03, <i>P</i> = 0.30). These results suggest that diffusion MRI in NAWM may be superior to white matter hyperintensity volumetrics when evaluating the role of white matter tract integrity on cognitive outcomes in people with relatively mild cerebrovascular pathology. These results also demonstrate that multi-domain spoken language analysis is sensitive to underlying white matter microstructure in participants with cerebrovascular disease without significant aphasia, supporting its value as a tool for assessing cognitive status.

Authors

Institutions

Publication Details

Journal
Brain Communications
Published
2025-01-01
DOI
https://doi.org/10.1093/braincomms/fcaf145
Citations
1
Primary Topic
Neurobiology of Language and Bilingualism
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

White matter tract correlations with spoken language in cerebrovascular disease

Bruce G. Pollock, Elena Leontieva, Morris Freedman, Sujeevini Sujanthan et al.
1 citations
Brain Communications
Neurobiology of Language and Bilingualism
1.43
article

White matter tract correlations with spoken language in cerebrovascular disease

Bruce G. Pollock, Elena Leontieva, Morris Freedman, Sujeevini Sujanthan, Jane Lawrence Dewar, T. J. Lang, Sherif Defrawy, Stephen C. Strother, Peter Kleinstiver, Robert Bartha, Dallas Seitz, Ekaterina A. Rogaeva, Julia Fraser, Wendy Lou, Stephen Pasternak, Melissa F. Holmes, Maria Carmela Tartaglia, Andrew Frank, Alisia Southwell, Donna Kwan, Alexander Havens, Athena Theyers, John F. Robinson, Karen Van Ooteghem, Stephen R. Arnott, Corinne E. Fischer, Paula McLaughlin, Derek Beaton, Yanina Sarquis Adamson, Allison A. Dilliott, Natalie Rashkovan, Wendy Hatch, Doug Munoz, Angela K. Troyer, Dar Dowlatshahi, Lorne Zinman, Agessandro Abrahão, Bill McIlroy, Mojdeh Zamyadi, Tom Steeves, Nuwan D. Nanayakkara, Alicia Peltsch, Kelly M. Sunderland, Brian Levine, John Turnbull, Chris Hudson, Miracle Ozzoude, Sali M.K. Farhan, Sean Symons, Katharine Aveni, Efrem D. Mandelcorn, Dennis E. Bulman, Don Brien, Manuel Montero‐Odasso, Brian Tan, Barry Greenberg, Tarek K. Rajji, Frederico Faria, Gustavo Saposnik, Mandar Jog, Ben Cornish, Michael Borrie, Brian C. Coe, Connie Marras, Sanjeev Kumar, Susan E. Bronskill, Elizabeth C. Finger, Courtney Berezuk, Malcolm A. Binns, Faryan Tayyari, Leanne K. Casaubon, Dana N Broberg, Alanna Black, Angela Roberts, Mahdi Ghani, Joel Ramirez, Demetrios J. Sahlas, J. B. Orange, Michael J. Strong, Sabrina Adamo, Ed Margolin, John Woulfe, David Tang-Wai, Christopher J.M. Scott, Ayman Hassan, David G. Munoz, Jennifer Mandzia, Roger A. Dixon, Mario Masellis, Rob Hegele, Christen L. Shoesmith, D.J. Grimes, Sandra Black, Seyyed MH Haddad, Richard H. Swartz
article en
1 citations

Abstract

Assessment of spoken language is a promising marker for cognitive impairment in individuals with cerebrovascular disease. However, the underlying neurological basis for spoken language beyond single words and sentences remains poorly defined in this cohort, particularly with respect to white matter. This study aimed to examine and compare white matter hyperintensity volumes and diffusion tensor metrics in normal-appearing white matter (NAWM) as potential correlates of spoken language performance. Baseline imaging and spoken language data were obtained from the cerebrovascular disease cohort of the Ontario Neurodegenerative Disease Research Initiative (<i>n</i> = 127; age: 55-85 years). Most participants had subclinical or very mild strokes, with very little to no aphasia symptoms. Spoken language samples were analysed to compute 10 different measures related to syntax, productivity, lexical diversity, fluency, and information content. Structural and diffusion MRI data were analysed to segment white matter hyperintensities and tracts. Normalized white matter hyperintensity volume, as well as average fractional anisotropy and mean diffusivity in the normal-appearing portion of eight white matter tracts, were correlated with the 10 spoken language measures using canonical correlation analyses. White matter and spoken language variate scores for individual participants then were correlated separately in male (<i>n</i> = 86) and female (<i>n</i> = 41) participants to probe potential sex differences. Spoken language performance was significantly associated with the fractional anisotropy (<i>r<sub>c</sub></i> = 0.51, <i>P</i> <i>=</i> 0.041) and mean diffusivity (<i>r<sub>c</sub></i> = 0.56, <i>P</i> <i>=</i> 0.011) of NAWM, particularly in the left superior longitudinal fasciculus, but not with white matter hyperintensity volumes (<i>r<sub>c</sub></i> = 0.41, <i>P</i> <i>=</i> 0.80) in the same tracts. Measures related to syntax, fluency, and information content loaded most strongly in the spoken language variate. No significant sex differences were found in NAWM microstructure, and female and male participants exhibited similarly strong associations between spoken language and NAWM microstructure (fractional anisotropy: <i>z</i> = 1.44, <i>P</i> = 0.15; mean diffusivity: <i>z</i> = 1.03, <i>P</i> = 0.30). These results suggest that diffusion MRI in NAWM may be superior to white matter hyperintensity volumetrics when evaluating the role of white matter tract integrity on cognitive outcomes in people with relatively mild cerebrovascular pathology. These results also demonstrate that multi-domain spoken language analysis is sensitive to underlying white matter microstructure in participants with cerebrovascular disease without significant aphasia, supporting its value as a tool for assessing cognitive status.

Brain CommunicationsVol. 7(3)
Northwestern University (US), Western University (CA), Dalhousie University (CA), Sunnybrook Health Science Centre (CA), 3M (United States) (US), Harvard University (US), University of Ottawa (CA), University of Toronto (CA), Queen's University (CA), Scarborough Health Network (CA), Ottawa Hospital (CA), Health Sciences Centre (CA), Nova Scotia Health Authority (CA), Baycrest Hospital (CA), Thunder Bay Regional Research Institute (CA), Regional Health (US), Ottawa Hospital Research Institute (CA), Sunnybrook Research Institute, Mass General Brigham (US), Case Western Reserve University (US), University of Maryland, College Park (US), NOSM University (CA)
ALS Association, University of Ottawa, Ontario Brain Institute, Government of Ontario, Centre for Addiction and Mental Health Foundation, Bruyère Research Institute, London Health Sciences Foundation, Canada Research Chairs, Faculty of Health Sciences, Queen's University
Quality Education
Openalex Percentile: Top 20%
Neurobiology of Language and Bilingualism
1.43
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.