The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals

Abstract

Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages.

Cognitive Variability during Middle-Age: Possible Association with Neurodegeneration and Cognitive Reserve

“…Also, multivariate analyses could be conducted in larger samples in order to investigate the interactive contribution of factors such as gender, depressive symptomatology, cognitive reserve, etc. (Ferreira et al, 2017b). In the current study, we did not find any partial contribution of gender and depressive symptomatology to deviation in the global deviation index.…”

Advances in Studying Brain Morphology: The Benefits of Open-Access Data

“…As an example of studying memory using brain morphology, one could examine the relationship between behavioral measures of memory performance and structural measures such as hippocampal volume across a large number of individuals or as differences between participant groups (e.g., den Heijer et al, 2012 ; Ferreira et al, 2017 ; Olsen et al, 2017 ; Ritter et al, 2017 ). In contrast, researchers using fMRI to assess memory would examine differences in brain activity related to memory during encoding or retrieval tasks (i.e., subsequent memory effect [SME] or retrieval success [RS], respectively), looking for temporal fluctuations in regional activation in within-subject contrasts (e.g., Reagh and Yassa, 2014 ; Richter et al, 2016 ; Chen et al, 2017 ; de Chastelaine et al, 2017 ; Madan et al, 2017 ).…”

Atrophy subtypes and the ATN classification scheme in Alzheimer’s disease

“…This result might seem unexpected since ADNI recruited mild to moderate AD patients, while typical AD would re ect full-blown AD at the highest degree of neurodegeneration. However, ADNI is a highly selective research cohort with strict inclusion criteria [12] that aimed to recruit the prototypical amnestic presentation of AD, which correlates with the typical AD subtype in neuropathological studies [32]. In addition, ADNI recruited patients with high education, which probably positively in uenced patients' cognitive reserve, possibly explaining why patients in ADNI have overt ATN and brain atrophy pro les, yet they are at mild to moderate clinical stages.…”

“…We evaluated AD subtypes in combination with ATN pro les in two cohorts: a homogeneous research-oriented cohort (the ADNI study: Alzheimer's Disease Neuroimaging Initiative), and a heterogeneous clinically oriented cohort (the KIDS study: Karolinska Imaging Dementia Study). Investigating AD subtypes and ATN pro les in cohorts with different characteristics is relevant because these subtypes are thought to result from risk factors, protective factors, and comorbid brain pathologies [5] that are differently represented in research-and clinically-oriented cohorts 12 . We hypothesized that the distribution of AD subtypes and ATN pro les would differ depending on cohort and demographic and clinical characteristics.…”