Consideration of sex and gender in Alzheimer's disease and related disorders from a global perspective

Mielke, Michelle M.; Aggarwal, Neelum T.; Vila‐Castelar, Clara; Agarwal, Puja; Arenaza‐Urquijo, Eider M.; Brett, Benjamin L.; Brugulat‐Serrat, Anna; DuBose, Lyndsey E.; Eikelboom, Willem S.; Flatt, Jason D.; Foldi, Nancy S.; Franzen, Sanne; Gilsanz, Paola; Li, Wei; McManus, Alison J.; Lent, Debora Melo van; Milani, Sadaf Arefi; Shaaban, C. Elizabeth; Stites, Shana D.; Sundermann, Erin E.; Suryadevara, Vidyani; Trani, Jean‐Francoise; Turner, Arlener D.; Vonk, Jet M.J.; Quiroz, Yakeel T.; Babulal, Ganesh M.

doi:10.1002/alz.12662

Cited by 44 publications

(53 citation statements)

References 273 publications

(496 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, sex and gender disparities and neighborhood disadvantage disparities need to be considered while studying resilience in AD/ADRD. The sex- and gender-specific changes in the balance between resilience and pathogenesis risk factors vary over the AD/ADRD disease course; however, the cause of such sex and gender differences is not clearly understood ( Mielke et al, 2022 ).…”

Section: Area Deprivation Index As a Surrogate Of Lifestyle And Morbi...mentioning

confidence: 99%

Area Deprivation Index as a Surrogate of Resilience in Aging and Dementia

2022

View full text Add to dashboard Cite

Area deprivation index (ADI), a tool used to capture the multidimensional neighborhood socioeconomic disadvantage across populations, is highly relevant to the field of aging and Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD). ADI is specifically relevant in the context of resilience, a broad term used to explain why some older adults have better cognitive outcomes than others. The goal of this mini-review is three-fold: (1) to summarize the current literature on ADI and its link to cognitive impairment outcomes; (2) suggest possible mechanisms through which ADI may have an impact on AD/ADRD outcomes, and (3) discuss important considerations when studying relations between ADI and cognitive as well as brain health. Though difficult to separate both the upstream factors that emerge from high (worse) ADI and all the mechanisms at play, ADI is an attractive proxy of resilience that captures multifactorial contributors to the risk of dementia. In addition, a life-course approach to studying ADI may allow us to capture resilience, which is a process developed over the lifespan. It might be easier to build, preserve or improve resilience in an environment that facilitates instead of hindering physical, social, and cognitively beneficial activities. Neighborhood disadvantage can adversely impact cognitive impairment risk but be at the same time a modifiable risk factor, amenable to policy changes that can affect communities.

show abstract

Section: Area Deprivation Index As a Surrogate Of Lifestyle And Morbi...mentioning

confidence: 99%

Area Deprivation Index as a Surrogate of Resilience in Aging and Dementia

2022

View full text Add to dashboard Cite

show abstract

“…Future studies would benefit from defining these constructs better in their analyses. 49 Finally, longitudinal studies are required to explore whether the kinds of classes identified behave differently over time with respect to brain health and how this relates to sex- and/or gender-related factors.…”

Section: Discussionmentioning

confidence: 99%

Associations of Sex, Age, and Cardiometabolic Risk Profiles With Brain Structure and Cognition

et al. 2022

View full text Add to dashboard Cite

Objectives:It is unknown whether there are sex-related profiles of cardiometabolic health that contribute differently to age-related changes in brain health during midlife. We studied how latent classes of middle-aged individuals clustering by age, sex, menopause and cardiometabolic health were associated with brain structure and cognitive performance.Methods:Health, brain and abdominal magnetic resonance imaging (MRI) data from the UK Biobank cohort (men and women >40 years in the United Kingdom) were used. We applied latent class analysis to identify groups of individuals based on age, sex, menopausal status and cardiometabolic health. We examined associations of class membership with brain volumes (total brain [TBV], grey matter [GMV], white matter [WMV], hippocampal [HV], white matter hyperintensities [WMHV]) and cognitive performance.Results:Data were available for 36,420 individuals (mean age 64.9 years, 48.5% women). Eight latent classes differing in age, sex and cardiometabolic risk were identified. Class 1 (reference class) included individuals with the lowest probability of older age and cardiometabolic risk, and they had the most positive associations with cognitive function and brain volumes. In those aged >60, but not in those aged 50-60 years, the negative associations of age with TBV, GMV and WMV were greater in the class comprising healthier older women than classes comprising older men of varying cardiometabolic and vascular health. There were no age-class interactions for cognitive test performance.Conclusions:Latent class analysis detected groups of middle-aged individuals clustering by cardiometabolic health. The relationship of age with brain volumes varies by sex, menopausal status and cardiometabolic health profile.

show abstract

“…In its first 4 years, the PNA enrolled 7 predoctoral trainees and 3 postdoctoral trainees from diverse disciplinary backgrounds including psychology, neuroscience, and epidemiology. Among the six trainees who have been in the program for more than 1 years, all completed core and interdisciplinary coursework, and seminars, and produced novel research findings and generate novel ideas based on a multidisciplinary perspective of ADRD, as demonstrated by their scientific productivity as PNA trainees (Alber et al, 2019;Shaaban et al, 2019aShaaban et al, ,b,c, 2021Shaaban et al, , 2022Cui et al, 2020;Johnson et al, 2020;Lin et al, 2020;Ly et al, 2020aLy et al, ,b, 2021Shaaban and Molad, 2020;Tian et al, 2020Tian et al, , 2022Aghjayan et al, 2021;Chahine et al, 2021;Ehrenkranz et al, 2021;Freed et al, 2021;Sprague, 2021;Sprague et al, 2021a,b;Yu et al, 2021;Donofry et al, 2022;Mielke et al, 2022;Silva et al, 2022). Four of 6 trainees submitted an NIH grant while in training, showing that using PNA resources enables them to conduct independent and rigorous research PNA trainees are committed to following a career in academic research.…”

Section: Lessons Learnedmentioning

confidence: 99%

A training program for researchers in population neuroimaging: Early experiences

Rosano

2022

Front. Neuroimaging

View full text Add to dashboard Cite

Recent advances in neuroimaging create groundbreaking opportunities to better understand human neurological and psychiatric diseases, but also bring new challenges. With the advent of more and more sophisticated and efficient multimodal image processing software, we can now study much larger populations and integrate information from multiple modalities. In consequence, investigators that use neuroimaging techniques must also understand and apply principles of population sampling and contemporary data analytic techniques. The next generation of neuroimaging researchers must be skilled in numerous previously distinct disciplines and so a new integrated model of training is needed. This tutorial presents the rationale for such a new training model and presents the results from the first years of the training program focused on population neuroimaging of Alzheimer's Disease. This approach is applicable to other areas of population neuroimaging.

show abstract

Consideration of sex and gender in Alzheimer's disease and related disorders from a global perspective

Cited by 44 publications

References 273 publications

Area Deprivation Index as a Surrogate of Resilience in Aging and Dementia

Area Deprivation Index as a Surrogate of Resilience in Aging and Dementia

Associations of Sex, Age, and Cardiometabolic Risk Profiles With Brain Structure and Cognition

A training program for researchers in population neuroimaging: Early experiences

Contact Info

Product

Resources

About