Despite the important role of written language in everyday life, abnormalities in functional written communication have been sparsely investigated in Primary Progressive Aphasia (PPA). Prior studies have analyzed written language separately in the three variants of PPA - nonfluent (nfvPPA), logopenic (lvPPA), and semantic (svPPA) - but have rarely compared them to each other or to spoken language. Manual analysis of written language can be a time-consuming process. We developed a program which uses a language parser and quantifies content units (CU) and total units (U) in written language samples. The program was used to analyze written and spoken descriptions of the WAB Picnic scene, based on a pre-defined CU corpus. We then calculated the ratio of CU to U (CU/U Ratio) as a measure of content density. Our cohort included 115 participants (20 control participants for written, 20 control participants for spoken, 28 participants with nfvPPA, 30 with lvPPA, and 17 with svPPA). We compared written language between patients with PPA and control participants and written to spoken language in patients with the three variants of PPA. Finally, we analyzed CU and U in relation to the Progressive Aphasia Severity Scale Sum of Boxes and the Clinical Dementia Rating Sum of Boxes. Our program identified CU with a validity of 99.7% (95%CI 99.5 to 99.8) compared to manual annotation of the samples. All patients with PPA wrote fewer total units than controls (p<0.001). Patients with lvPPA (p=0.013) and svPPA (0.004) wrote fewer CU than controls. The CU/U Ratio was higher in nfvPPA and svPPA than controls (p=0.019 in both cases), but no different between lvPPA patients and controls (p=0.962). Participants with lvPPA (p<0.001) and svPPA (p=0.04) produced fewer CU in written samples compared to spoken. A two-way ANOVA showed all groups produced fewer units in written samples compared to spoken (p<0.001). However, the decrease in written CU compared to spoken was smaller than the decrease in written units compared to spoken in participants with PPA, resulting in a larger written CU/U Ratio when compared to spoken language (p<0.001). nfvPPA patients produced correlated written and spoken CU (R=0.5, p=0.009) and total units (R=0.64, p<0.001), but this was not the case for lvPPA or svPPA. Considering all PPA patients, fewer CU were produced in those with greater aphasia severity (PASS SoB, R=-0.24, p=0.04) and dementia severity (CDR SoB, R=-0.34, p=0.004). In conclusion, we observed reduced written content in patients with PPA compared to controls, with a preference for content over non-content units in patients with nfvPPA and svPPA. When comparing written to spoken language, we observed a similar "telegraphic" style in both modalities in patients with nfvPPA, which was different from patients with svPPA and lvPPA, who use significantly less non-content units in writing than in speech. Lastly, we show how our program provides a time-efficient tool, which could enable feedback and tracking of writing as an important feature of language and cognition.
Background and Objectives.Patients with Primary Progressive Aphasia (PPA) have gradually progressive language deficits during the initial phase of the illness. As the underlying neurodegenerative disease progresses, PPA patients start losing independent functioning due to the development of non-language cognitive or behavioral symptoms. The timeline of this progression from the mild cognitive impairment stage to the dementia stage of PPA is variable across patients. Here, in a sample of PPA patients, we measured the magnitude of cortical atrophy within functional networks thought to subserve diverse cognitive and affective functions. We then evaluated the utility of this measure as a predictor of time to subsequent progression to dementia in PPA.Methods.PPA patients with largely independent daily function were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit. All patients underwent an MRI scan at baseline. Cortical atrophy was then estimated relative to a group of amyloid-negative cognitively normal control participants. For each patient, we measured the time between the baseline visit and the subsequent visit at which dementia progression was documented or last observation. Simple and multivariable Cox regression models were used to examine the relationship between cortical atrophy and the likelihood of progression to dementia.Results:Forty-nine PPA patients (mean age = 66.39 ± 8.36 years, 59.2% females) and 25 controls (mean age = 67.43 ± 4.84 years, 48% females) were included in the data analysis. Greater baseline atrophy in not only the left language network (hazard ratio [HR] = 1.47, 95% CI = 1.17-1.84) but also in the frontoparietal control (1.75, 1.25-2.44), salience (1.63, 1.25-2.13), default mode (1.55, 1.19-2.01), and ventral frontotemporal (1.41, 1.16-1.71) networks was associated with a higher risk of progression to dementia. A multivariable model identified contributions of the left frontoparietal control (1.94, 1.09-3.48) and ventral frontotemporal (1.61, 1.09-2.39) networks in predicting dementia progression, with no additional variance explained by the language network (0.75, 0.43-1.31).Discussion:These results suggest that baseline atrophy in cortical networks subserving non-language cognitive and affective functions is an important predictor of progression to dementia in PPA. This measure should be included in precision medicine models of prognosis in PPA.
Despite the important role of written language in everyday life, abnormalities in functional written communication have been sparsely investigated in primary progressive aphasia. Prior studies have analyzed written language separately in each of the three variants of primary progressive aphasia – but have rarely compared them to each other or to spoken language. Manual analysis of written language can be a time-consuming process. We therefore developed a program which quantifies content units and total units in written or transcribed language samples. We analyzed written and spoken descriptions of the Western Aphasia Battery Picnic scene, based on a pre-defined content unit corpus. We calculated the ratio of content units to units as a measure of content density. Our cohort included 115 participants (20 controls for written, 20 controls spoken, 28 participants with nonfluent variant primary progressive aphasia, 30 logopenic variant, 17 semantic variant). Our program identified content units with a validity of 99.7% (95%CI 99.5-99.8). All patients wrote fewer units than controls (p<0.001). Patients with the logopenic variant (p=0.013) and the semantic variant (0.004) wrote fewer content units than controls. The content-unit-to-unit ratio was higher in the nonfluent and semantic variants than controls (p=0.019), but no different in the logopenic variant (p=0.962). Participants with the logopenic (p<0.001) and semantic (p=0.04) variants produced fewer content units in written compared to spoken descriptions. All variants produced fewer units in written samples compared to spoken (p<0.001). However, due to a relatively smaller decrease in written content units, we observed a larger content-unit-to-unit ratio in writing over speech (p<0.001). Written and spoken content units (r=0.5, p=0.009) and total units (r=0.64, p<0.001) were significantly correlated in patients with nonfluent variant, but this was not the case for logopenic or semantic. Considering all patients with primary progressive aphasia, fewer content units were produced in those with greater aphasia severity (Progressive Aphasia Severity Scale Sum of Boxes, r=-0.24, p=0.04) and dementia severity (Clinical Dementia Rating scale Sun of Boxes, r=-0.34, p=0.004). In conclusion, we observed reduced written content in patients with primary progressive aphasia compared to controls, with a preference for content over non-content units in patients with the nonfluent and semantic variants. We observed a similar “telegraphic” style in both language modalities in patients with the nonfluent variant. Lastly, we show how our program provides a time-efficient tool, which could enable feedback and tracking of writing as an important feature of language and cognition.
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