Forskningsartikler

Abstract

Background: High blood pressure and poor cardiorespiratory fitness are independent risk factors for dementia. However, few studies have examined if combined longitudinal patterns of these modifiable risk factors are associated with dementia risk.

Methods: In this prospective cohort study, we used data from the population-based HUNT Study, Norway. We applied group-based multidimensional trajectory modeling to identify age-specific multidimensional trajectories of SBP, DBP and estimated cardiorespiratory fitness across three surveys (HUNT1, 1984-86 – HUNT3, 2006-08). Dementia was diagnosed in the HUNT4 70+ substudy in 2017-19. We used multivariate logistic regression to estimate odds ratios (ORs) and risk differences (RDs) of dementia.

Results: In total, 7594 participants (54.9% women) were included, with a mean age of 44.7 (SD 6.3) years at HUNT1. Dementia was diagnosed in 1062 (14.0%) participants. We identified two multidimensional trajectories throughout adulthood within three age groups: one with higher SBP and DBP, and lower estimated cardiorespiratory fitness (the poorer group), and one with lower SBP and DBP, and higher cardiorespiratory fitness (the better group). After adjustment for sex, APOE ε4 status, education, marital status and diabetes, the better group had consistently lower risk of dementia in all age groups with the lowest OR in the middle-aged group of 0.63 (95% CI 0.51, 0.78) with corresponding RD of -0.07 (95% CI -0.10, -0.04).

Conclusions: Having a beneficial multidimensional trajectory of SBP, DBP and cardiorespiratory fitness in adulthood was associated with reduced dementia risk. Aiming for optimal SBP, DBP and estimated cardiorespiratory fitness throughout adulthood may reduce dementia risk.

Maren Lerfald, Heather Allore, Tom I L Nilsen, Rannveig S Eldholm, Nicolas Martinez-Velilla, Geir Selbæk & Linda Ernstsen

Introduction: Individuals with Alzheimer’s disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study’s goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes.
Methods:
Genome-wide associationmeta-analysis of 9988 AD participants from six source studies with participants characterized for AD+PAD+A, and a joint phenotype (AD+A+P).
Results:
AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms.AD+Awas positively correlatedwith anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereasAD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations.
Discussion:
AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development.

Inga Margret Antonsdottir, Byron Creese, Lambertus Klei, Mary Ann A. DeMichele-Sweet, Elise A. Weamer, Pablo Garcia-Gonzalez, Marta Marquie, Mercè Boada, Emilio Alarcón-Martín,  Sergi Valero, NIA-LOAD Family Based Study Consortium, Alzheimer’s Disease Genetics Consortium (ADGC), AddNeuroMed Consortium, Yushi Liu, Basavaraj Hooli, Dag Aarsland, Geir Selbaek, Sverre Bergh, Arvid Rongve, Ingvild Saltvedt, Håvard K. Skjellegrind, Bo Engdahl, Ole A. Andreassen, Barbara Borroni, Patrizia Mecocci, Yehani Wedatilake, Richard Mayeux, Tatiana Foroud, Agustín Ruiz, Oscar L. Lopez, M. Ilyas Kamboh, Clive Ballard, Bernie Devlin, Constantine Lyketsos & Robert A. Sweet

Background: A timely diagnosis of dementia can be beneficial for providing good support, treatment, and care, but the diagnostic rate remains unknown and is probably low.

Objective: To determine the dementia diagnostic rate and to describe factors associated with diagnosed dementia.

Methods: This registry linkage study linked information on research-based study diagnoses of all-cause dementia and subtypes of dementias, Alzheimer’s disease, and related dementias, in 1,525 participants from a cross-sectional population-based study (HUNT4 70+) to dementia registry diagnoses in both primary-care and hospital registries. Factors associated with dementia were analyzed with multiple logistic regression.

Results: Among those with research-based dementia study diagnoses in HUNT4 70+, 35.6% had a dementia registry diagnosis in the health registries. The diagnostic rate in registry diagnoses was 19.8% among home-dwellers and 66.0% among nursing home residents. Of those with a study diagnosis of Alzheimer’s disease, 35.8% (95% confidence interval (CI) 32.6-39.0) had a registry diagnosis; for those with a study diagnosis of vascular dementia, the rate was 25.8% (95% CI 19.2-33.3) and for Lewy body dementias and frontotemporal dementia, the diagnosis rate was 63.0% (95% CI 48.7-75.7) and 60.0% (95% CI 43.3-75.1), respectively. Factors associated with having a registry diagnosis included dementia in the family, not being in the youngest or oldest age group, higher education, more severe cognitive decline, and greater need for help with activities of daily living.

Conclusions: Undiagnosed dementia is common, as only one-third of those with dementia are diagnosed. Diagnoses appear to be made at a late stage of dementia.

Linda Gjøra, Bjørn Heine Strand, Sverre Bergh, Ingunn Bosnes, Aud Johannessen, Gill Livingston, Håvard Kjesbu Skjellegrind & Geir Selbæk

Abstract

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

Esten H. Leonardsen, Karin Persson, Edvard Grødem, Nicola Dinsdale, Till Schellhorn, James M. Roe, Didac Vidal-Piñeiro, Øystein Sørensen, Tobias Kaufmann, Eric Westman, Andre Marquand, Geir Selbæk, Ole A. Andreassen, Thomas Wolfers, Lars T. Westlye & Yunpeng Wang

Background and Objectives
The cognitive reserve hypothesis posits that cognitively stimulating work delays the onset of mild cognitive impairment (MCI) and dementia. However, the effect of occupational cognitive demands across midlife on the risk of these conditions is unclear.
Methods
Using a cohort study design, we evaluated the association between registry-based trajectories of occupational cognitive demands from ages 30–65 years and clinically diagnosed MCI and dementia in participants in the HUNT4 70+ Study (2017–19). Group-based trajectory modeling identified trajectories of occupational cognitive demands, measured by the routine task intensity (RTI) index (lower RTI indicates more cognitively demanding occupation) from the Occupational Information Network. Multinomial regression was implemented to estimate the relative risk ratios (RRRs) of MCI and dementia, after adjusting for age, sex, education, income, baseline hypertension, obesity, diabetes, psychiatric impairment, hearing impairment, loneliness, smoking status, and physical inactivity assessed at HUNT1-2 in 1984–1986 and 1995–1997. To handle missing data, we used inverse probability weighting to account for nonparticipation in cognitive testing and multiple imputation.
Results
Based on longitudinal RTI scores for 305 unique occupations, 4 RTI trajectory groups were identified (n = 7,003, 49.8% women, age range 69–104 years): low RTI (n = 1,431, 20.4%), intermediate-low RTI (n = 1,578, 22.5%), intermediate-high RTI (n = 2,601, 37.1%), and high RTI (n = 1,393, 19.9%). Participants in the high RTI group had a higher risk of MCI (RRR 1.74, 95% CI 1.41–2.14) and dementia (RRR 1.37, 95% CI 1.01–1.86), after adjusting for age, sex, and education compared with participants in the low RTI group. In a sensitivity analysis, controlling for income and baseline health-related factors, the point estimates were not appreciably changed (RRR 1.66, 95% CI 1.35–2.06 for MCI, and RRR 1.31, 95% CI 0.96–1.78 for dementia).
Discussion
People with a history of cognitively stimulating occupations during their 30s, 40s, 50s, and 60s had a lower risk of MCI and dementia older than 70 years, highlighting the importance of occupational cognitive stimulation during midlife for maintaining cognitive function in old age. Further research is required to pinpoint the specific occupational cognitive demands that are most advantageous for maintaining later-life cognitive function.

Trine H Edwin, Asta K Håberg, Ekaterina Zotcheva, Bernt Bratsberg, Astanand Jugessur, Bo Engdahl, Catherine Bowen, Geir Selbæk, Hans-Peter Kohler, Jennifer R Harris, Sarah E Tom, Steinar Krokstad, Teferi Mekonnen, Yaakov Stern, Vegard F Skirbekk, Bjørn H Strand

Abstract

Introduction: People with Down syndrome (DS) have high risk of developing Alzheimer’s disease (AD). This study examined mean ages of AD diagnosis and associations with co-occurring conditions among adults with DS from five European countries.

Methods: Data from 1335 people with DS from the Horizon 21 European DS Consortium were used for the analysis.

Results: Mean ages of AD diagnosis ranged between 51.4 (SD 7.0) years (United Kingdom) and 55.6 (SD 6.8) years (France). Sleep-related and mental health problems were associated with earlier age of AD diagnosis. The higher number of co-occurring conditions the more likely the person with DS is diagnosed with AD at an earlier age.

Discussion: Mean age of AD diagnosis in DS was relatively consistent across countries. However, co-occurring conditions varied and impacted on age of diagnosis, suggesting that improvements can be made in diagnosing and managing these conditions to delay onset of AD in DS.

Highlights: Mean age of AD diagnosis was relatively consistent between countries Sleep problems and mental health problems were associated with earlier age of AD diagnosis APOE ε4 carriers were diagnosed with AD at an earlier age compared to non-carriers Number of co-occurring conditions was associated with earlier age of AD diagnosis No differences between level of intellectual disability and mean age of AD diagnosis.

Frode Kibsgaard Larsen, R. Asaad Baksh, Eimear McGlinchey, Ellen Melbye Langballe, Bessy Benejam, Jessica Beresford-Webb, Mary McCarron, Antonia Coppus, Segolene Falquero, Juan Fortea, Johannes Levin, Sandra V. Loosli, Ruth Mark, Anne-Sophie Rebillat, Shahid Zaman & Andre Strydom

Background: More women are living with dementia than men worldwide and there is a need to investigate causes for this female preponderance. While reproductive factors have been investigated as risk factors, the results are conflicting. We aim to clarify this using a large cohort with a long observation time, adjusting for multiple health and lifestyle variables and encompassing a wider range of cognitive impairment.

Objective: To study the association between menopause age, menarche age and risk of and risk of mild cognitive impairment (MCI) and dementia.

Setting: The Trøndelag Health study (HUNT), a longitudinal population health study in Norway (1984–2019).

Participants: Women who were ≥70 years in 2017–2019 were assessed for cognitive impairment.

Measurements: Data on menopause age and menarche age were obtained from questionnaires. Diagnosis of MCI or dementia was set using a standardised procedure by a diagnostic group of nine physicians. Multinomial logistic regression was used to study the association between menopause age, menarche age and risk of MCI and dementia with adjustment for birth year, education, smoking, ApoE4, number of children, diabetes, body mass index, alcohol use and physical inactivity.

Results: We evaluated 5314 women where 900 (16.9%) had dementia, and 1747 (32.8%) had MCI. Multiple adjusted relative risk ratio (RRR) and 95% confidence intervals (CI) for dementia were: 0.96(95%CI 0.95–0.98) (p<0.001) for menopause age, 0.97(95%CI 0.94–0.99) (p=0.007) for natural menopause age (excluding hysterectomy and/or oophorectomy<55 years) and 0.97(95%CI 0.95–0.99) (p<0.001) for reproductive span (menopause age minus menarche age). Menopause age <45years was associated with a 56% higher risk compared to mean menopause age 50 years. We found no significant associations between menarche age and dementia and no associations with MCI.

Conclusions: Older menopause age and longer reproductive span corresponding to longer oestrogen exposure were associated with a lower dementia risk. Future studies should explore therapeutical options to offset this risk in women.

Yehani Wedatilake, C. Myrstad, S. E. Tom, B. H. Strand, S. Bergh & G. Selbæk

Objectives: This research project investigated how family carers in Norway experienced delivering iCST, their need for supervision and the potential for co-occupation.

Methods: Reflexive thematic analysis was used to understand the experiences of 11 carers using iCST for 8 wk. Three semi-structured interviews were conducted with each participant, including a pre-assessment of caregiver burden and a rating of dementia severity.

Results: Most carers described the manual as self-instructive. Some felt overwhelmed when starting iCST. It was important to plan and individualise the sessions to the specific needs of the person with dementia. After delivering iCST the carers described new insights into the person with dementia’s resources and challenges. Obstacles to doing iCST were related to the context, the manual or to specific challenges linked to the person with dementia or to the carer. Most participants described positive experiences, in which shared interaction, engagement and mastery were common.

Conclusion: When the carer understands the iCST programme as a tool and adapts it to the specific needs of the person with dementia then co-occupation and positive interactions happen. However, some carers would benefit from supervision and the iCST programme did not address all persons with dementia.

Kristine G. Madsø, Rita Weum & Torhild Holthe

Bcakground and purpose
The aims were to compare the novel regional brain volumetric measures derived by the automatic software NeuroQuant (NQ) with clinically used visual rating scales of medial temporal lobe atrophy (MTA), global cortical atrophy-frontal (GCA-f), and posterior atrophy (PA) brain regions, assessing their diagnostic validity, and to explore if combining automatic and visual methods would increase diagnostic prediction accuracy.

Methods
Brain magnetic resonance imaging (MRI) examinations from 86 patients with subjective and mild cognitive impairment (i.e., non-dementia, n = 41) and dementia (n = 45) from the Memory Clinic at Oslo University Hospital were assessed using NQ volumetry and with visual rating scales. Correlations, receiver operating characteristic analyses calculating area under the curves (AUCs) for diagnostic accuracy, and logistic regression analyses were performed.

Results
The correlations between NQ volumetrics and visual ratings of corresponding regions were generally high between NQ hippocampi/temporal volumes and MTA (r = −0.72/−0.65) and between NQ frontal volume and GCA-f (r = −0.62) but lower between NQ parietal/occipital volumes and PA (r = −0.49/−0.37). AUCs of each region, separating non-dementia from dementia, were generally comparable between the two methods, except that NQ hippocampi volume did substantially better than visual MTA (AUC = 0.80 vs. 0.69). Combining both MRI methods increased only the explained variance of the diagnostic prediction substantially regarding the posterior brain region.

Conclusions
The findings of this study encourage the use of regional automatic volumetry in locations lacking neuroradiologists with experience in the rating of atrophy typical of neurodegenerative diseases, and in primary care settings.

Karin Persson, Maria L. Barca, Trine Holt Edwin, Lena Cavallin-Eklund, Gro Gujord Tangen, Hanneke F. M. Rhodius-Meester, Geir Selbæk, Anne-Brita Knapskog og Knut Engedal