Hippocampal subfield volumes in COVID-19: a preliminary multicenter study using 7T MRI

Background: Hippocampal formation atrophy is a well-established imaging biomarker of several neurological diseases, including Alzheimer\u27s disease, temporal lobe epilepsy, and schizophrenia. The hippocampus is divided into subfields that have different functions and vary in sensitivity to different diseases. This study investigates the potential interaction between COVID-19 and the various hippocampus subfields, which may shed light on the long-term neurological consequences of the virus. Method: We obtained high-resolution T1-weighted (T1w) and T2-weighted (T2w) MRI images using 7T scanners located at three sites in two countries: Pittsburgh (n=14) and Texas (San Antonio and Houston) (n=40) in the USA, and Nottingham, UK (n=33). We evaluated the hippocampus subfields using the ASHS package [1-3]. Imaging sets of 51 subjects with minimal or no manual segmentation corrections (Figures 1 and 2) were included in the analysis. We conducted T-tests with Bonferroni correction, adjusting for age and intracranial volume to identify the differences in hippocampus subfield volumes across groups. Result: Participants who needed admission into the ICU due to Covid-19 showed a significantly lower (p-value=0.0034) left CA1 volume compared to participants who did not require ICU (Figure 3). In addition, several other non-significant trends were observed. Conclusion: Our preliminary findings suggest that Covid-19 may impact the hippocampus, particularly in patients who required intensive care. However, the study - as of to date - has a small sample size and lacks a comparison group with patients who were admitted into ICU for acute illnesses other than Covid-19. Additionally, longitudinal data is needed to track the long-term effects of the disease on the hippocampal subfields

Genetic Risk Score Predicts Late-Life Cognitive Impairment

Introduction. A family history of Alzheimer's disease is a significant risk factor for its onset, but the genetic risk associated with possessing multiple risk alleles is still poorly understood. Methods. In a sample of 95 older adults (Mean age = 75.1, 64.2% female), we constructed a genetic risk score based on the accumulation of risk alleles in BDNF, COMT, and APOE. A neuropsychological evaluation and consensus determined cognitive status (44 nonimpaired, 51 impaired). Logistic regression was performed to determine whether the genetic risk score predicted cognitive impairment above and beyond that associated with each gene. Results. An increased genetic risk score was associated with a nearly 4-fold increased risk of cognitive impairment (OR = 3.824, P = .013) when including the individual gene polymorphisms as covariates in the model. Discussion. A risk score combining multiple genetic influences may be more useful in predicting late-life cognitive impairment than individual polymorphisms

Subjective Cognitive Decline in Older Adults: An Overview of Self-Report Measures Used Across 19 International Research Studies

Research increasingly suggests that subjective cognitive decline (SCD) in older adults, in the absence of objective cognitive dysfunction or depression, may be a harbinger of non-normative cognitive decline and eventual progression to dementia. Little is known, however, about the key features of self-report measures currently used to assess SCD. The Subjective Cognitive Decline Initiative (SCD-I) Working Group is an international consortium established to develop a conceptual framework and research criteria for SCD (Jessen et al., 2014, Alzheimers Dement 10, 844-852). In the current study we systematically compared cognitive self-report items used by 19 SCD-I Working Group studies, representing 8 countries and 5 languages. We identified 34 self-report measures comprising 640 cognitive self-report items. There was little overlap among measures- approximately 75% of measures were used by only one study. Wide variation existed in response options and item content. Items pertaining to the memory domain predominated, accounting for about 60% of items surveyed, followed by executive function and attention, with 16% and 11% of the items, respectively. Items relating to memory for the names of people and the placement of common objects were represented on the greatest percentage of measures (56% each). Working group members reported that instrument selection decisions were often based on practical considerations beyond the study of SCD specifically, such as availability and brevity of measures. Results document the heterogeneity of approaches across studies to the emerging construct of SCD. We offer preliminary recommendations for instrument selection and future research directions including identifying items and measure formats associated with important clinical outcome

O2‐05‐03: Birth Cohort Effects in Memory Function and Practice Effects From Epidemiological Studies of Cognitive Impairment and Dementia

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153286/1/alzjjalz201606419.pd

Does a cognitive stress test predict progression from mild cognitive impairment to dementia equally well in clinical versus population-based settings?

ABSTRACTBackground:Evidence suggests that semantic interference may be a sensitive indicator of early dementia. We examined the utility of the Semantic Interference Test (SIT), a cognitive stress memory paradigm which taps proactive and retroactive semantic interference, for predicting progression from mild cognitive impairment (MCI) to dementia in both a clinical and a population-based sample. Participants with MCI in the clinical (n = 184) and population-based (n = 435) samples were followed for up to four years. We employed receiver operating characteristic (ROC) methods to establish optimal thresholds for four different SIT indices. Threshold performance was compared in the two samples using logistic and Cox proportional hazard regression models. Within four years, 42 (22.8%) MCI individuals in the clinical sample and 45 (10.3%) individuals in the population-based sample progressed to dementia. Overall classification accuracy of SIT thresholds ranged from 61.4% to 84.8%. Different subtests of the SIT had slightly different performance characteristics in the two samples. However, regression models showed that thresholds established in the clinical sample performed similarly in the population sample before and after adjusting for demographics and other baseline neuropsychological test scores. Despite differences in demographic composition and progression rates, baseline SIT scores predicted progression from MCI to dementia similarly in both samples. Thresholds that best predicted progression were slightly below thresholds established for distinguishing between amnestic MCI and cognitively normal subjects in clinical practice. This confirms the utility of the SIT in both clinical and population-based samples and establishes thresholds most predictive of progression of individuals with MCI