Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

Underrepresented and Underserved Populations in Neurological Research.

Underserved and underrepresented populations have historically been excluded from neurological research. This lack of representation has implications for translation of research findings into clinical practice given the impact of social determinants of health on neurological disease risk, progression, and outcomes. Lack of inclusion in research is driven by individual-, investigator-, and study-level barriers as well as larger systemic injustices (e.g., structural racism, discriminatory practices). Although strategies to increase inclusion of underserved and underrepresented populations have been put forth, numerous questions remain about the most effective methodology. In this article, we highlight inclusivity patterns and gaps among the most common neurological conditions and propose best practices informed by our own experiences in engagement of local community organizations and collaboration efforts to increase underserved and underrepresented population participation in neurological research.

Characterizing Multimorbidity Prevalence and Adverse Outcomes in Ethnically and Culturally Diverse Sub-Populations in India: Gaps, Opportunities, and Future Directions.

India is a large middle-income country and has surpassed China in overall population, comprising 20% of the global population (over 1.43 billion people). India is experiencing a major demographic shift in its aging population. Chronic diseases are common among older adults and can be persistent over the life course, lead to the onset of disability, and be costly. Among older adults in India, the existence of multiple comorbid chronic conditions (i.e., multimorbidity) is rapidly growing and represents a burgeoning public health burden. Prior research identified greater rates of multimorbidity (e.g., overweight/obesity diabetes, hypertension, cardiovascular disease, stroke, and malignancies) in minority populations in the United States (U.S.); however, limited studies have attempted to characterize multimorbidity among older adult sub-populations residing in India. To address this gap, we conducted a narrative review of studies on multimorbidity using the data from the Longitudinal Aging Study of India (LASI), the largest nationally representative longitudinal survey study of adults in India. Our definition of multimorbidity was the presence of more than two conditions in the same person. Our findings, based on 15 reviewed studies, aim to (1) characterize the definition and measurement of multimorbidity and to ascertain its prevalence in ethnically and culturally diverse sub-populations in India; (2) identify adverse outcomes associated with multimorbidity in the Indian adult population; and (3) identify gaps, opportunities, and future directions.

Contribution of Global Amyloid-PET Imaging for Predicting Future Cognition in the MEMENTO Cohort.

BACKGROUND AND OBJECTIVES: Global amyloid-PET is associated with cognition and cognitive decline, but most research on this association does not account for past cognitive information. We assessed the prognostic benefit of amyloid-PET measures for future cognition when prior cognitive assessments are available, evaluating the added value of amyloid measures beyond information on multiple past cognitive assessments. METHODS: The French MEMENTO cohort (a cohort of outpatients from French research memory centers to improve knowledge on Alzheimer disease and related disorders) includes older outpatients with incipient cognitive changes, but no dementia diagnosis at inclusion. Global amyloid burden was assessed using positron emission tomography (amyloid-PET) for a subset of participants; semiannual cognitive testing was subsequently performed. We predicted mini-mental state examination (MMSE) scores using demographic characteristics (age, sex, marital status, and education) alone or in combination with information on prior cognitive measures. The added value of amyloid burden as a predictor in these models was evaluated with percent reduction of the mean squared error (MSE). All models were conducted separately for evaluating the added value of dichotomous amyloid positivity status compared with a continuous amyloid-standardized uptake-value ratio. RESULTS: Our analytic sample comprised 510 individuals who underwent amyloid-PET scans with at least 4 MMSE assessments. The mean age at the PET scan was 71.6 (standard deviation 7.4) years; 60.7% were female. The median follow-up was 4.6 years (interquartile range: 0.9 years). Adding amyloid burden when adjusting for only demographic characteristics reduced the MSE of predictions by 5.08% (95% CI 0.97%-10.86%) and 12.64% (95% CI 3.35%-25.28%) for binary and continuous amyloid, respectively. If the model included 1 past MMSE measure, the MSE improvement was 3.51% (95% CI 1.01%-7.28%) when adding binary amyloid and 8.83% (95% CI 2.63%-16.37%) when adding continuous amyloid. Improvements in model fit were smaller with the addition of amyloid burden when more than 1 past cognitive assessment was included. For all models incorporating past cognitive assessments, differences in predictions amounted to a fraction of 1 MMSE point on average. DISCUSSION: In a clinical setting, global amyloid burden did not appreciably improve cognitive predictions when past cognitive assessments were available. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT02164643.

Associations of Everyday and Lifetime Experiences of Discrimination With Willingness to Undergo Alzheimer Disease Predictive Testing.

BACKGROUND AND OBJECTIVES: Rapid developments in Alzheimer disease (AD) biomarker research suggest that predictive testing may become widely available. To ensure equal access to AD predictive testing, it is important to understand factors that affect testing interest. Discrimination may influence attitudes toward AD testing, particularly among racially and ethnically minoritized populations, because of structural racism in health care systems. This study examined whether everyday or lifetime discrimination experiences shape interest in AD predictive testing. METHODS: In the 2010 and 2012 biennial Health and Retirement Study waves, respondents were randomly selected to complete questions on interest in receiving free testing that could determine whether they would develop AD in the future. The exposures were everyday discrimination (6 items) and lifetime discrimination (7 items); both were transformed into a binary variable. Logistic regression models predicting interest in AD testing were controlled for deciles of propensity scores for each discrimination measure. Odds ratios were re-expressed as risk differences (RDs). RESULTS: Our analytic sample included 1,499 respondents. The mean age was 67 (SD = 10.2) years, 57.4% were women, 65.7% were White, and 80% endorsed interest in AD predictive testing. Most of the participants (54.7%) experienced everyday discrimination in at least one domain; 24.1% experienced major lifetime discrimination in at least one domain. Those interested in predictive testing were younger (66 vs 70 years) and more likely to be Black (20% vs 15%) or Latinx (14% vs 8%) than participants uninterested in testing. The probability of wanting an AD test was not associated with discrimination for Black (RD everyday discrimination = -0.026; 95% CI [-0.081 to 0.029]; RD lifetime discrimination = -0.012; 95% CI [-0.085 to 0.063]) or Latinx (RD everyday discrimination = -0.023, 95% CI [-0.082 to 0.039]; RD lifetime discrimination = -0.011; 95% CI [-0.087 to 0.064]) participants. DISCUSSION: Despite historical and contemporary experiences of discrimination, Black and Latinx individuals express interest in AD testing. However, Black and Latinx individuals remain underrepresented in AD research, including research on AD testing. Interest in personalized information about dementia risk may be a pathway to enhance their inclusion in research and clinical trials.

"Hang Ups, Let Downs, Bad Breaks, Setbacks": Impact of Structural Socioeconomic Racism and Resilience on Cognitive Change Over Time for Persons Racialized as Black.

Introduction: Older adults racialized as Black experience higher rates of dementia than those racialized as White. Structural racism produces socioeconomic challenges, described by artist Marvin Gaye as "hang ups, let downs, bad breaks, setbacks" that likely contribute to dementia disparities. Robust dementia literature suggests socioeconomic factors may also be key resiliencies. Methods: We linked state-level data reflecting the racialized landscape of economic opportunity across the 20th Century from the U.S. Census (1930-2010) with individual-level data on cognitive outcomes from the U.S. Health and Retirement Study participants racialized as Black. A purposive sample of participants born after the Brown v. Board ruling (born 1954-59) were selected who completed the modified Telephone Interview for Cognitive Status between 2010 and 2020 (N=1381). We tested associations of exposure to structural racism and resilience before birth, and during childhood, young-adulthood, and midlife with cognitive trajectories in mid-late life using mixed-effects regression models. Results: Older adults born in places with higher state-level structural socioeconomic racism experienced a more rapid cognitive decline in later life compared to those with lower levels of exposure. In addition, participants born in places with higher levels of state-level structural socioeconomic resilience experienced slower cognitive change over time than their counterparts. Discussion: These findings reveal the impact of racist U.S. policies enacted in the past that influence cognitive health over time and dementia risk later in life.

Empathy as a crucial skill in disrupting disparities in global brain health.

Brain health refers to the state of a person's brain function across various domains, including cognitive, behavioral and motor functions. Healthy brains are associated with better individual health, increased creativity, and enhanced productivity. A person's brain health is intricately connected to personal, social and environmental factors. Racial, ethnic, and social disparities affect brain health and on the global scale these disparities within and between regions present a hurdle to brain health. To overcome global disparities, greater collaboration between practitioners and healthcare providers and the people they serve is essential. This requires cultural humility driven by empathy. Empathy is a core prosocial value, a cognitive-emotional skill that helps us understand ourselves and others. This position paper aims to provide an overview of the vital roles of empathy, cooperation, and interdisciplinary partnerships. By consciously integrating this understanding in practice, leaders can better position themselves to address the diverse challenges faced by communities, promote inclusivity in policies and practices, and further more equitable solutions to the problem of global brain health.