5613510 effects of regional brain volume on cognition in sickle cell anaemia: a developmental perspective

Cognitive decline, related at least in part to reduced processing speed and lower working memory, is a major problem in paediatric and adult patients with sickle cell anaemia (SCA)1,2 and affects quality of life. Multiple studies investigating the association between quantitative and qualitative neuroimaging findings and cognition have had mixed results. Hence, the aetiology of cognitive decline in this population is not clearly understood. Cerebral atrophy on magnetic resonance imaging is noted in the literature but few studies have investigated the association between brain volumes and cognition. White matter microstructural integrity and white matter hyperintensities have been associated with reduced processing speed index (PSI).3 However no study has investigated the association between white matter volumes and PSI in the SCA population. Total subcortical volumes have also been noted to be lower in SCA children and adults. Only one study has investigated the association between total subcortical volumes and working memory index (WMI) in adults.4 Moreover, several studies in the past have noted age related decline in total brain volume as well neurodevelopmental delay in grey matter volume growth.5,6 Most of the developmental trajectory data in the literature comes from longitudinal data sets with limited samples and without control groups. Hence, for the purpose of this study, we investigated the association between regional brain volumes (white matter volumes and total subcortical volumes) and cognition (processing speed index and working memory index) in 129 SCA patients aged 8 – 64 years (66 male) and 50 controls (21 males). Participants were enrolled in two studies - the Sleep Asthma Cohort (SAC) and the Prevention of Morbidity in SCA (POMS) trial. We hypothesized that white matter volumes would predict processing speed index and total subcortical volumes would predict working memory index in SCA patients as well as controls. We also hypothesized that the developmental trajectories for regional brain volumes and cognitive variables would differ between patients and controls. Separate multiple linear regression models for males and females revealed that WMV predicted processing speed index(p=.019) and total subcortical volumes predicted working memory index (p=.025) in male patients only. Age (p=.003) and socioeconomic status (p=.03) also independently predicted PSI in male patients. Individual subcortical regions predicting WMI were statistically significant for left and right thalamus only in male patients. Haemoglobin and age emerged as the best predictors of cognitive decline in patients. Comparison of developmental trajectories between patients and controls revealed that only processing speed was significantly delayed at 8 years. The rate of development for all variables was lower in SCA patients and age-related decline was accelerated in patients as compared to controls. We speculate that early cerebral haemodynamic compromise may contribute to long term cognitive decline in patients. We also highlight that male SCA patients are particularly vulnerable to SCA disease severity. Hence, timely intervention to stabilise haemoglobin levels, especially in males, should be considered. Limitations include lack of stratification by SCI and age (adults and children separately) and the possibility that we were underpowered to detect effects in females. References 1. Wang W, Enos L, Gallagher D, Thompson R, Guarini L, Vichinsky E, Wright E, Zimmerman R, Armstrong FD; Cooperative Study of Sickle Cell Disease. Neuropsychologic performance in school-aged children with sickle cell disease: a report from the Cooperative Study of Sickle Cell Disease. J Pediatr. 2001 Sep;139(3):391-7. 2. Ampomah MA, Drake JA, Anum A, Amponsah B, Dei-Adomakoh Y, Anie K, Mate-Kole CC, Jonassaint CR, Kirkham FJ. A case-control and seven-year longitudinal neurocognitive study of adults with sickle cell disease in Ghana. Br J Haematol. 2022 Aug 26. 3. Stotesbury H, Kirkham FJ, Kölbel M, Balfour P, Clayden JD, Sahota S, Sakaria S, Saunders DE, Howard J, Kesse-Adu R, Inusa B, Pelidis M, Chakravorty S, Rees DC, Awogbade M, Wilkey O, Layton M, Clark CA, Kawadler JM. White matter integrity and processing speed in sickle cell anemia. Neurology. 2018 Jun 5;90(23):e2042-e2050. 4. Mackin RS, Insel P, Truran D, Vichinsky EP, Neumayr LD, Armstrong FD, Gold JI, Kesler K, Brewer J, Weiner MW; Neuropsychological Dysfunction and Neuroimaging Adult Sickle Cell Anemia Study Group. Neuroimaging abnormalities in adults with sickle cell anemia: associations with cognition. Neurology. 2014 Mar 11;82(10):835-41. 5. Chen R, Krejza J, Arkuszewski M, Zimmerman RA, Herskovits EH, Melhem ER. Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: A preliminary study. Adv Med Sci. 2017 Mar;62(1):151-157. 6. Darbari DS, Eigbire-Molen O, Ponisio MR, Milchenko MV, Rodeghier MJ, Casella JF, McKinstry RC, DeBaun MR. Progressive loss of brain volume in children with sickle cell anemia and silent cerebral infarct: A report from the silent cerebral infarct transfusion trial. Am J Hematol. 2018 Dec;93(12):E406-E408.