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. 2022 Dec:120:105-116.
doi: 10.1016/j.neurobiolaging.2022.08.013. Epub 2022 Sep 2.

Functional connectivity to the premotor cortex maps onto longitudinal brain neurodegeneration in progressive apraxia of speech

Irene Sintini  1 , Joseph R Duffy  2 , Heather M Clark  2 , Rene L Utianski  2 , Hugo Botha  2 , Mary M Machulda  3 , Matthew L Senjem  4 , Edythe A Strand  5 , Christopher G Schwarz  6 , Val J Lowe  6 , Clifford R Jack  6 , Keith A Josephs  2 , Jennifer L Whitwell  6
Affiliations

Functional connectivity to the premotor cortex maps onto longitudinal brain neurodegeneration in progressive apraxia of speech

Irene Sintini et al. Neurobiol Aging. 2022 Dec.

Abstract

Primary progressive apraxia of speech (PPAOS) is a neurodegenerative motor speech disorder affecting the ability to produce speech. If agrammatic aphasia is present, it can be referred to as the non-fluent/agrammatic variant of primary progressive aphasia (nfvPPA). We investigated whether resting-state functional MRI (rs-fMRI) connectivity from disease "epicenters" correlated with longitudinal gray matter atrophy and hypometabolism in nfvPPA and PPAOS. Eighteen nfvPPA and 23 PPAOS patients underwent clinical assessment, structural MRI, rs-fMRI, and [18F] fluorodeoxyglucose (FDG)-PET at baseline and ∼2 years follow-up. Rates of neurodegeneration in nfvPPA and PPAOS correlated with functional connectivity to the premotor, motor, and frontal cortex. Connectivity to the caudate and thalamus was more strongly associated with rates of hypometabolism than atrophy. Connectivity to the left Broca's area was more strongly associated with rates of atrophy and hypometabolism in nfvPPA. Finally, functional connectivity to a network of regions, and not to a single epicenter, correlated with rates of neurodegeneration in PPAOS and nfvPPA, suggesting similar biological mechanisms driving disease progression, with regional differences related to language.

Keywords: Aphasia; Apraxia of speech; Functional connectivity; Longitudinal neurodegeneration; Multimodal imaging.

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Conflict of interest statement

Declaration of competing interest M.L.S. has owned stocks, within the past 12 months, in Align Technology, Inc., Inovio Pharmaceuticals Inc., LHC Group, Inc., Mesa Laboratories, Inc., and Natus Medical Inc., unrelated to the current study. V.J.L. consults for Bayer Schering Pharma, Piramal Life Sciences, Life Molecular Imaging, Eisai Inc., AVID Radiopharmaceuticals, and Merck Research and receives research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals. C.R.J. serves on a scientific advisory board for Eli Lilly & Company, as a speaker for Eisai and on an independent data safety monitoring board for Roche but he receives no personal compensation from any commercial entity. All other authors report no competing interests for this study.

Figures

Figure 1.
Figure 1.. Group-level longitudinal neurodegeneration.
Group-level images of annualized rates of MRI grey matter atrophy (A) and annualized rates of change of FDG-PET SUVR (B) in nfvPPA and PPAOS. Group-average voxel maps are visualized using BrainNet Viewer (https://www.nitrc.org/projects/bnv/). T-score maps are visualized in Fslview (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslView) for a better representation of both cortical and subcortical patterns. Group-average cortical regional data are visualized using the Brainnetome atlas available in the ggseg package in R (https://doi.org/10.5281/zenodo.5569249), while subcortical data are mapped from the Brainnetome onto the aseg atlas available in ggseg for visualization purposes only.
Figure 2.
Figure 2.. Correlations between baseline functional connectivity and longitudinal neurodegeneration.
Each region of the Brainnetome atlas is colored-coded based on the Pearson’s R correlation coefficient between group-average functional connectivity from that region and measures of longitudinal rates of atrophy (A) and hypometabolism (B) in nfvPPA and PPAOS. A negative correlation (in blue) indicates that a stronger functional connectivity to the region is associated with faster rates of neurodegeneration across all other connected regions.
Figure 3.
Figure 3.. Epicenters’ functional connectivity and rates of atrophy.
Correlations between annualized rates of MRI grey matter atrophy and functional connectivity (FC) or shortest path to the epicenter (SPE) to the dorsolateral Brodmann area 6 of left superior frontal gyrus (Brainnetome SFG_7_4_L) and the caudal dorsolateral Brodmann area 6 of the left precentral gyrus (Brainnetome PrG_6_2_L) in nfvPPA (A, B) and PPAOS (C, D). Correlations that remained statistically significant (p<0.05) after Bonferroni correction for multiple comparisons are marked with an asterisk. ROI-to-ROI functional connectivity from these regions is displayed as red dots on the brain renders (p<0.001); red dots represent functionally connected ROIs, while blue dots represent anti-correlated ROIs. R = Pearson’s correlations coefficient. Rd = Pearson’s partial correlations coefficient corrected for Euclidean distance from the epicenter. CI = 5%-95% confidence intervals.
Figure 4.
Figure 4.. Epicenters’ functional connectivity and rates of hypometabolism.
Correlations between annualized rates of change of FDG-PET SUVR and functional connectivity (FC) or shortest path to the epicenter (SPE) to the medial Brodmann area 8 of the superior frontal gyrus (Brainnetome SFG_7_1_L), right dorsal caudate (Brainnetome BG_6_5_R) and left and right caudal temporal thalamus (Brainnetome Tha_8_7_R and Tha_8_7_L) in nfvPPA (A, B, C) and PPAOS (D, E, F). Correlations that remained statistically significant (p<0.05) after Bonferroni correction for multiple comparisons are marked with an asterisk. ROI-to-ROI functional connectivity from these regions is displayed on brain renders (p<0.001). R = Pearson’s correlations coefficient. Rd = Pearson’s partial correlations coefficient corrected for Euclidean distance from the epicenter. CI = 5%-95% confidence intervals.
Figure 5.
Figure 5.. Functional connectivity of the left Broca’s area and rates of neurodegeneration.
Correlations between annualized rates of neurodegeneration and functional connectivity (FC) or shortest path to the epicenter (SPE) to the left Broca’s area in nfvPPA (A, B) and PPAOS (C, D). Correlations that remained statistically significant (p<0.05) after Bonferroni correction for multiple comparisons are marked with an asterisk. ROI-to-ROI functional connectivity from these regions is displayed on brain renders (p<0.001). R = Pearson’s correlations coefficient. Rd = Pearson’s partial correlations coefficient corrected for Euclidean distance from the epicenter. CI = 5%-95% confidence intervals.
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References

    1. Albrecht F, Ballarini T, Neumann J, and Schroeter ML. 2019. ‘FDG-PET hypometabolism is more sensitive than MRI atrophy in Parkinson’s disease: A whole-brain multimodal imaging meta-analysis’, Neuroimage-Clinical, 21. - PMC - PubMed
    1. Armstrong MJ, Litvan I, Lang AE, Bak TH, Bhatia KP, Borroni B, Boxer AL, Dickson DW, Grossman M, Hallett M, Josephs KA, Kertesz A, Lee SE, Miller BL, Reich SG, Riley DE, Tolosa E, Troster AI, Vidailhet M, and Weiner WJ. 2013. ‘Criteria for the diagnosis of corticobasal degeneration’, Neurology, 80: 496–503. - PMC - PubMed
    1. Botha H, Duffy JR, Whitwell JL, Strand EA, Machulda MM, Schwarz CG, Reid RI, Spychalla AJ, Senjem ML, Jones DT, Lowe V, Jack CR, and Josephs KA. 2015. ‘Classification and clinicoradiologic features of primary progressive aphasia (PPA) and apraxia of speech’, Cortex, 69: 220–36. - PMC - PubMed
    1. Botha H, Utianski RL, Whitwell JL, Duffy JR, Clark HM, Strand EA, Machulda MM, Tosakulwong N, Knopman DS, Petersen RC, Jack CR, Josephs KA, and Jones DT. 2018. ‘Disrupted functional connectivity in primary progressive apraxia of speech’, Neuroimage-Clinical, 18: 617–29. - PMC - PubMed
    1. Brambati SM, Amici S, Racine CA, Neuhaus J, Miller Z, Ogar J, Dronkers N, Miller BL, Rosen H, and Gorno-Tempini ML. 2015. ‘Longitudinal gray matter contraction in three variants of primary progressive aphasia: A tenser-based morphometry study’, Neuroimage-Clinical, 8: 345–55. - PMC - PubMed

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