An Evaluation of Cross-Cultural Adaptations of Social Cognition Testing: A Systematic Review

Social cognition remains one of the most difficult cognitive domains to assess in diverse populations due to a lack of culturally appropriate tools. This study systematically reviewed literature on neuropsychological tests for social cognition that have been translated, adapted, are cross-cultural, or are assembled for diverse, specifically "Global South," populations. The aim was to identify assessments appropriate for diverse populations, outline and evaluate their methodological approaches, and provide procedural recommendations for future research. The PRISMA systematic review search strategy produced 10,957 articles, of which 287 were selected for full-text screening. The study had to include a neuropsychological assessment of social cognition. The full text of the resulting 287 articles was then screened; the study had to include a translated, adapted, cross-cultural test, or an assembled test for Global South populations. Eighty-four articles were included in this study: 24 for emotion recognition, 45 for theory of mind, 9 for moral reasoning, and six for social cognition in general. Overall, there were 31 translations, 27 adaptations, 14 cross-cultural tests, and 12 assembled tests for Global South populations. Regarding quality, 35 were of low quality, 27 were of moderate quality, and 22 were high quality. This study provides an overview of social cognition tests modified or assembled for diverse populations and gives examples of methodological procedures. It highlights the variability in procedure quality and provides possible reasons for this variability. Finally, it suggests a need to report rigorous modification and assembly procedure in order to have modified and assembled social cognition tests appropriate for diverse populations.

Multiancestry analysis of the HLA locus in Alzheimer's and Parkinson's diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Diagnosis and Care Use for People with Young-Onset Dementia in Primary Care in the Netherlands

BACKGROUND

Timely diagnosis and adequate care is important for persons with young-onset dementia (YOD) and their caregivers, due to the high impact of the disease. Initiating care can be difficult for the general practitioner (GP) and other healthcare professionals.

OBJECTIVE

Provide insight in the care use of persons with YOD and identify factors influencing care use.

METHODS

A primary care register was used for this study. Information on the care use of persons with YOD was extracted from the GPs written notes. Information entailed time until start of care use, reasons and factors influencing the GP's decision, and reasons and factors influencing actual care use were included. Analyses included quantitative explorative descriptive analyses, and qualitative manifest content analyses.

RESULTS

75 persons with YOD were included in this study. The main reason for GPs to refer for diagnosis was concerns of caregivers. After diagnosis, 72% of the persons were assigned a case manager, 42.7% received day care, and 44% were admitted to a long-term care facility. A higher percentage of persons without a case manager was admitted to a long-term care facility (64%) compared to the persons with a case manager (36%). Reasons for not initiating care were reluctancy of the persons with YOD or their caregivers, the person deceased, or because the GP did not refer for care.

CONCLUSION

Care use differed between persons due to different needs and reasons. Although most persons with YOD receive care in the years after diagnosis, there are still factors that could be improved.

Global incidence of young-onset dementia: A systematic review and meta-analysis

INTRODUCTION

Reliable data on the incidence rates for young-onset dementia (YOD) are lacking, but are necessary for research on disease etiology and to raise awareness among health care professionals.

METHODS

We performed a systematic review and meta-analysis on population-based studies on the incidence of YOD, published between January 1, 1990 and February 1, 2022, according to Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines. Data were analyzed using random-effects meta-analyses. Results were age-standardized, and heterogeneity was assessed by subgroup analyses and meta-regression.

RESULTS

Sixty-one articles were included. Global age-standardized incidence rates increased from 0.17/100,000 in age 30 to 34 years, to 5.14/100,000 in age 60 to 64 years, giving a global total age-standardized incidence rate of 11 per 100,000 in age 30 to 64. This corresponds to 370,000 new YOD cases annually worldwide. Heterogeneity was high and meta-regression showed geographic location significantly influenced this heterogeneity.

DISCUSSION

This meta-analysis shows the current best estimate of YOD incidence. New prospective cohort studies are needed.

Provisional consensus on the nomenclature and operational definition of dementia at a young age, a Delphi study

OBJECTIVES

Dementia at a young age differs from late onset dementia in pathology and care needs. This requires further research to improve the understanding of this group, support and service provision. Aim of current study is to reach consensus on the terminology and operational definition (i.e., age-related criteria and possible causes) of dementia at a young age, to aid further research.

METHODS

A classical Delphi technique was used to transform opinions into group consensus by using an online survey. In three rounds statements regarding (1) terminology, (2) age-related criteria, and (3) aetiologies that can be considered as causes of dementia at a young age were sent to international experts in the field to give their opinions and additional comments on the statements.

RESULTS

Forty-four experts responded and full consensus was reached on 22 out of 35 statements. Young-onset dementia emerged as the term of preference. Provisional consensus was found for the use of age 65 at symptom onset as preferred cut-off age. Consensus was reached on the inclusion of 15 out of 22 aetiologies and categories of aetiologies as potential cause for dementia at a young age.

CONCLUSIONS

A clear term and operational definition have been reached. Although beneficial for conducting future research to gain more insight in pathology and care needs of young people living with dementia, still consensus about some details is lacking. To reach consensus about these details and implications for use in research and clinical practice, the organisation of an in person consensus meeting is advised.

Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

BACKGROUND

We previously found temporoparietal-predominant atrophy patterns in the behavioral variant of Alzheimer's disease (bvAD), with relative sparing of frontal regions. Here, we aimed to understand the clinico-anatomical dissociation in bvAD based on alternative neuroimaging markers.

METHODS

We retrospectively included 150 participants, including 29 bvAD, 28 "typical" amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other diagnostic groups on glucose metabolism and metabolic connectivity measured by [18F]FDG-PET, and on subcortical gray matter and white matter hyperintensity (WMH) volumes measured by MRI. A receiver-operating-characteristic-analysis was performed to determine the neuroimaging measures with highest diagnostic accuracy.

RESULTS

bvAD and tAD showed predominant temporoparietal hypometabolism compared to controls, and did not differ in direct contrasts. However, overlaying statistical maps from contrasts between patients and controls revealed broader frontoinsular hypometabolism in bvAD than tAD, partially overlapping with bvFTD. bvAD showed greater anterior default mode network (DMN) involvement than tAD, mimicking bvFTD, and reduced connectivity of the posterior cingulate cortex with prefrontal regions. Analyses of WMH and subcortical volume showed closer resemblance of bvAD to tAD than to bvFTD, and larger amygdalar volumes in bvAD than tAD respectively. The top-3 discriminators for bvAD vs. bvFTD were FDG posterior-DMN-ratios (bvADbvFTD, area under the curve [AUC] range 0.85-0.91, all p < 0.001). The top-3 for bvAD vs. tAD were amygdalar volume (bvAD>tAD), MRI anterior-DMN-ratios (bvAD

CONCLUSIONS

Subtle frontoinsular hypometabolism and anterior DMN involvement may underlie the prominent behavioral phenotype in bvAD.

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Key Words

• Alzheimer’s disease
• Behavior
• Frontotemporal dementia
• MRI
• PET

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MESH Headings

• Alzheimer Disease/diagnostic imaging
• Frontotemporal Dementia/diagnostic imaging
• Gray Matter
• Humans
• Magnetic Resonance Imaging
• Retrospective Studies

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Grants

• R01-AG045611 NIA NIH HHS
• K24 AG045333 NIA NIH HHS
• P01 AG003991 NIA NIH HHS
• P30 AG062422 NIA NIH HHS
• P01 AG019724 NIA NIH HHS
• R01 AG045611 NIA NIH HHS
• National Institute on Aging
• ZonMw

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Affiliation(s)

Ellen H. Singleton Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Yolande A. L. Pijnenburg Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Carole H. Sudre School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
Colin Groot Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Elena Kochova Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Frederik Barkhof Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
Renaud La Joie Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
Howard J. Rosen Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
William W. Seeley Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
Bruce Miller Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
M. Jorge Cardoso School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK Translational Imaging Group, CMIC, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
Janne Papma Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands
Philip Scheltens Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Gil D. Rabinovici Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, USA
Rik Ossenkoppele Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands Clinical Memory Research Unit, Lund University, Lund, Sweden

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Automatic normative quantification of brain tissue volume to support the diagnosis of dementia: A clinical evaluation of diagnostic accuracy

Objectives

To assesses whether automated brain image analysis with quantification of structural brain changes improves diagnostic accuracy in a memory clinic setting.

Methods

In 42 memory clinic patients, we evaluated whether automated quantification of brain tissue volumes, hippocampal volume and white matter lesion volume improves diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared to visual interpretation. Reference data were derived from a dementia-free aging population (n = 4915, aged >45 years), and were expressed as age- and sex-specific percentiles. Experienced radiologists determined the most likely imaging-based diagnosis based on structural brain MRI using three strategies (visual assessment of MRI only, quantitative normative information only, or a combination of both). Diagnostic accuracy of each strategy was calculated with the clinical diagnosis as the reference standard.

Results

Providing radiologists with only quantitative data decreased diagnostic accuracy both for AD and FTD compared to conventional visual rating. The combination of quantitative with visual information, however, led to better diagnostic accuracy compared to only visual ratings for AD. This was not the case for FTD.

Conclusion

Quantitative assessment of structural brain MRI combined with a reference standard in addition to standard visual assessment may improve diagnostic accuracy in a memory clinic setting.

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Brain imaging from an individual patient can be compared to population-derived reference data to determine deviation from the population average.

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Age adjusted reference values of brain volume improve accuracy of dementia diagnosis in a memory clinic, especially for AD.

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These reference values should be interpreted in conjunction with visual assessment of brain MRI's to achieve this benefit.