Changes in cortical thickness along the Alzheimer disease continuum in people with Down syndrome
Authors: Kennedy James Tyler , Dincer Aylin , Thippabhotla Sharmila , Roman June , Wisch Julie K. , Gordon Brian A. , Boerwinkle Anna H. , Flores Shaney , Chen Charles D. , Benzinger Tammie L.S. , Klunk William E , Rafii Michael S , O'Bryant Sid E. , Price Julie C , Yassa Michael A. , Sathishkumar Mithra , McMillan Liv , Brickman Adam M. , Lao Patrick J. , Laymon Charles M , Krinsky‐McHale Sharon J , Lai Florence , Rosas H. Diana , Hartley Sigan , Zaman Shahid , Lott Ira T , Silverman Wayne , Lee Joseph H. , Allegri Ricardo Francisco , Berman Sarah , Chhatwal Jasmeer P. , Chui Helena C , Cruchaga Carlos , Farlow Martin R. , Goate Alison , Day Gregory S. , Graff‐Radford Neill R , Jucker Mathias , Lee Jae‐Hong , Levin Johannes , Martins Ralph N , Mori Hiroshi , Perrin Richard J. , Salloway Stephen , Sanchez‐Valle Raquel , Xiong Chengjie , Karch Celeste M. , Hassenstab Jason J. , McDade Eric , Bateman Randall J. , Handen Benjamin L. , Head Elizabeth , Mapstone Mark , Christian Bradley T. , Ances Beau , Schofield Peter R , Network Dominantly Inherited Alzheimer ,   the Alzheimer’s Biomarker Consortium‐Down Syndrome
Published: December 2023

Background

Triplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal‐dominant AD1, but not DS‐related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology.

Method

Cross‐sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium‐Down Syndrome (106 amyloid‐/cognitively unimpaired, nonclinical, 20% reserved for receiver‐operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV452) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster‐wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired.

Result

Significant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal‐dominant AD (.547/.540)1. Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres.

Conclusion

CT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment.

1. Dincer (2020). NeuroImage: Clinical, 28, 102491.

2. Su (2019). Alzheimer’s Dement, 11, 180‐190.