Annegret Habich

Regional brain atrophy has been observed in dementia with Lewy bodies (DLB), yet determinants of regional vulnerability remain unclear. Using imaging transcriptomics, we examined whether normative gene expression patterns relate to regional atrophy in DLB. We included 164 DLB patients (49 women) and 164 age- and sex-matched healthy controls from three European centres and the Mayo Clinic, USA. Volumetric atrophy was quantified from T1-weighted MRI across 58 left-hemispheric regions using w -scores. Normative expression of twelve genes implicated in alpha-synuclein, beta-amyloid, and tau pathology was extracted from the Allen Human Brain Atlas. DLB patients showed diffuse atrophy across most regions. In the full cohort, normative expression of MAPT , PINK1 , and PSEN2 predicted regional atrophy after correction for spatial autocorrelation, although none survived multiple-testing correction. In the Mayo Clinic sub-cohort, expression of APP , BIN1 , GBA , MAPT , PINK1 , SNCA , and TMEM175 significantly predicted atrophy and survived multiple-testing correction. Random forest models did not outperform spatial null models in the full cohort, but PARK7 , PINK1 , and PSEN2 consistently emerged as important predictors. A significant global model was observed in the Mayo Clinic sub-cohort, driven by GBA , LRP1 , and PINK1 . These findings suggest that normative gene expression partially contributes to regional brain atrophy in DLB.

Background: While patients along the dementia with Lew bodies (DLB) continuum show widespread neurodegeneration, the determinants of this regional neurodegeneration remain largely unexplored. The underlying alpha‐synuclein pathology is hypothesized to spread along structural connections with affected brain regions undergoing neurodegeneration. We aimed to determine whether brain regions that are more closely connected to amygdala and brainstem, i.e. two suggested origins of the alpha‐synuclein pathology, exhibit greater volume reductions compared to more distantly connected regions. Additionally, we investigated whether regions that are more integrated in the brain network overall exhibit greater volume reductions compared to less integrated regio ns . Method: We included 80 patients along the DLB continuum and 65 cognitively healthy controls (HCs) from the Newcastle cohort of the European DLB consortium. Volumetric differences between DLB patients and HCs were quantified in 122 brain regions from T1‐weighted MRI, using averaged w‐scores. Tractography of white matter pathways between brain regions was performed on diffusion‐weighted images from DLB patients to build an average structural network. The distance of brain regions to amygdala and brain stem, and the regions’ integration in the network were calculated using graph theoretical network measures. Lastly, we correlated network measures with regional volumetric w‐scores. Result: Most brain regions showed lower volumes in patients along the DLB continuum compared with HCs, with neurodegeneration being most pronounced in temporal and parietal lobes. Regions more closely connected to the amygdala showed more volume reductions. In contrast, distance to the brainstem did not significantly correlate with regional w‐scores. Likewise, the integration of brain regions within the structural network did not significantly correlate with regional w‐scores. Conclusion: Our results emphasize that structural connections with the amygdala predict regional neurodegeneration, suggesting that the amygdala is an important relay region for the spread of the alpha‐synuclein pathology. Moreover, our findings support the use of imaging biomarkers to track disease progression in the absence of a topographic biomarker for the alpha‐synuclein pathology.

Cognitive impairment is required to diagnose mild cognitive impairment with Lewy bodies (MCI-LB). However, associations of impairments across cognitive domains remain unclear. In this cross-sectional study, we investigated these associations by assessing the cognitive connectome of MCI-LB patients compared with healthy controls (HC), mild cognitive impairment due to Alzheimer’s disease (MCI-AD), and dementia with Lewy bodies (DLB). Using the National Alzheimer’s Coordinating Center database, we built cognitive connectomes for MCI-LB ( n = 88), HC ( n = 3703), MCI-AD ( n = 1789), and DLB ( n = 104) by correlating 24 cognitive measures. We compared global and nodal network measures of centrality (importance of cognitive measure), integration (communication across cognitive measures), and segregation (specialisation of cognitive measures) between groups. For global measures, MCI-LB showed lower segregation than HC, with no significant differences from MCI-AD, and lower integration) and higher segregation than DLB. For nodal measures, MCI-LB compared with HC and MCI-AD showed differences in executive and memory measures, respectively. MCI-LB showed several nodal differences compared with DLB, involving executive, processing speed/attention, and language measures. Our findings suggest that MCI-LB involves early changes in the cognitive connectome, particularly reduced segregation that becomes more pronounced at the DLB stage and shows overlap with MCI-AD, offering insights into cognitive impairment in MCI-LB.

Cognition plays a central role in the diagnosis and characterization of dementia with Lewy bodies (DLB). However, the complex associations among cognitive deficits in different domains in DLB are largely unknown. To characterize these associations, we investigated and compared the cognitive connectome of DLB patients, healthy controls (HC), and Alzheimer’s disease patients (AD). We obtained data from the National Alzheimer’s Coordinating Center. We built cognitive connectomes for DLB (n = 104), HC (n = 3703), and AD (n = 1985) using correlations among 24 cognitive measures mapping multiple cognitive domains. Connectomes were compared using global and nodal graph measures of centrality, integration, and segregation. For global measures, DLB showed a higher global efficiency (integration) and lower transitivity (segregation) than HC and AD. For nodal measures, DLB showed higher global efficiency in most measures, higher participation (centrality) in free-recall memory, processing speed/attention, and executive measures, and lower local efficiency (segregation) than HC. Compared with AD, DLB showed lower nodal strength and local efficiency, especially in memory consolidation. The cognitive connectome of DLB shows a loss of segregation, leading to a loss of cognitive specialization. This study provides the data to advance the understanding of cognitive impairment and clinical phenotype in DLB, with implications for differential diagnosis.

Background: Patterns of regional atrophy and hypometabolism have been observed in dementia with Lewy bodies (DLB). However, determinants of regional vulnerability to structural and functional neurodegeneration remain largely unexplored. First, we investigated the association between regional gene expression and grey matter volumes in probable DLB patients. Since hypometabolism presumably precedes overt brain atrophy, we additionally investigate the association between regional gene expression and hypometabolism in DLB.Method: To investigate the association between gene expression and regional volumes, 165 DLB patients along with 165 age‐ and sex‐matched healthy controls from three European centres and the Mayo Clinic (USA) were included. Regional volumes were quantified from MRI using SPM12 in 112 cortical, subcortical, and cerebellar brain regions, and compared between groups, using w‐scores. Regional expression data of seven genes involved in the formation and degradation of pathological protein aggregates (APOE, APP, BIN1, GBA, MAPT, SNCA, TMEM175) was extracted from six healthy donors from the Allen Human Brain Atlas and correlated with regional volumetric w‐scores. To assess the predictive value of regional gene expression on regional volumes we used Gaussian stepwise backwards linear regression including all seven genes as predictors. To investigate the association between gene expression and hypometabolism, we are currently applying the same analysis pipeline to FDG‐PET data of 139 DLB patients from 8 European centres.Result: Most brain regions showed lower volumes in DLB patients compared to healthy controls, with differences being most pronounced in occipital and parietal lobes. Regional expression of APOE correlated positively with regional volumes in DLB. Conversely, regional expression of MAPT correlated negatively with regional volumes. Both APOE and MAPT gene expression were significant predictors of regional volumes in the regression analysis. None of the other gene expression values was significantly associated with regional volumes in DLB.Conclusion: Our findings show that regional expression of genes associated with the abnormal accumulation of amyloid and tau, common co‐pathologies in DLB, partially account for the brain atrophy pattern observed in DLB patients. Analyses are ongoing for the hypometabolism pattern. Our finding emphasises the relevance of co‐pathologies in predicting atrophy progression and identifying potential targets for future disease‐modifying treatments.

During ageing, different cognitive functions decline at different rates. Additionally, cognitive reserve may influence inter-individual variability in age-related cognitive decline. These complex relationships can be studied by constructing a so-called cognitive connectome and characterising it with advanced graph-theoretical network analyses. This study examined the effect of cognitive reserve on the cognitive connectome across age. A total of 334 cognitively healthy participants were stratified into early middle age (37–50 years; n = 110), late middle age (51–64 years; n = 106), and elderly (65–78 years; n = 118) groups. Within each age group, individuals were subdivided into high and low cognitive reserve. For each subgroup, a cognitive connectome was constructed based on correlations between 47 cognitive variables. Applying graph theory, different global network measures were compared between the groups. Graph-theoretical network analyses revealed that individuals with high cognitive reserve were characterized by a stable cognitive connectome across age groups. High cognitive reserve groups only differed in modularity. In contrast, individuals with low cognitive reserve showed a marked reconfiguration of cognitive connectomes across age groups with differences extending over a variety of network measures including network strength, global efficiency, modularity, and small-worldness. Our results suggest a stabilizing effect of cognitive reserve on the cognitive connectome. Gaining further insights into these findings and underlying mechanisms will contribute to our understanding of age-related cognitive decline and guide the development of strategies to preserve cognitive function in ageing.

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer’s disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)—parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), yet sex differences in patterns of neurodegeneration in DLB remain largely unexplored. Here, we test whether grey matter networks differ between sexes in DLB and compare these findings to sex differences in healthy controls. In this cross-sectional study, we analysed clinical and neuroimaging data of patients with DLB and cognitively healthy controls matched for age and sex. Grey matter networks were constructed by pairwise correlations between 58 regional volumes after correction for age, intracranial volume, and centre. Network properties were compared between sexes and diagnostic groups. Additional analyses were conducted on w-scored data to identify DLB-specific sex differences. Data from 119 (68.7 ± 8.4 years) men and 45 women (69.9 ± 9.1 years) with DLB, and 164 healthy controls were included in this study. Networks of men had a lower nodal strength compared to women. In comparison to healthy women, the grey matter networks of healthy men showed a higher global efficiency, modularity, and fewer modules. None of the network measures showed significant sex differences in DLB. Comparing DLB patients with healthy controls revealed global differences in women and more local differences in men. Modular analyses showed a more distinct demarcation between cortical and subcortical regions in men compared with women. While topologies of grey matter networks differed between sexes in healthy controls, those sex differences were diluted in DLB patients. These findings suggest a disease-driven convergence of neurodegenerative patterns in women and men with DLB, which may inform precision medicine in DLB.

Background: This study aimed to assess the comparative efficacy of monotherapy and combined therapy of cholinesterase inhibitors plus memantine on cognition in AD and determine efficacy across doses for these pharmacological drugs.Method: The screening of 2,113 articles were initiated. Finally, forty randomized controlled trials (RCTs) from PubMed, Web of Science, and Scopus databases inception to the end of Dec. 2022 were finally included in this review. The included RCTs contain donepezil, rivastigmine, galantamine and memantine alone or in any combination of them were compared with placebo in terms of MMSE score. The mean difference (MD) in MMSE score was considered as the effect size of efficacy. The quality of the RCTs were appraised using the Cochrane risk‐of‐bias tool (RoB‐2). An additive network meta‐analysis (NMA) was applied to compare the efficacy of the drugs. Trends of efficacy across doses for each available treatment were checked using a dose‐response modeling. Finally, P‐score as a probability of being the most effective treatment, was used to rank the treatments. All statistical analyses were done using netmeta and dosresmeta R packages. The study protocol was registered in the PROSPERO (CRD42022358469).Result: These RCTs included 16,785 AD patients with mean age 73 (SD = 3.5) yrs., and weight 64.5 (SD = 5.55) kg. Of these patients, 65.15% were women. The median follow‐up time was 6 (range = 3‐48) months. The main NMA results showed that galantamine 32mg/day (MD = 3.71; 95% CI = 2.21, 5.21; P‐score = 0.89), donepezil 10mg/day combined with memantine 20mg/day (MD = 3.27; 95% CI = 1.79, 4.76; P‐score = 0.83), and then galantamine 24mg/day (MD = 3.02; 95% CI = 2.19, 3.84; P‐score = 0.79) were significantly the most effective treatments compared with placebo, respectively. According to the sub‐group analysis of stages, donepezil 10mg/day combined with memantine 20mg/day (MD = 4.78; 95% CI = 2.86, 6.71) and galantamine 32mg/day (MD = 3.81; 95% CI = 2.20, 5.34) were recommended for moderate to severe and mild to moderate AD patients, respectively. Moreover, we found there was a significant positive linear trend of efficacy across doses of galantamine.Conclusion: Monotherapy with a high dose of galantamine or the combination of donepezil plus memantine have the most favorable effects on cognition for 6 months follow up in AD patients.

Objectives Cognition plays a central role for diagnosing and characterizing dementia with Lewy bodies (DLB). However, the complex associations among cognitive functions are largely unknown in DLB. To fill this gap, we compared the cognitive connectome of DLB patients, healthy controls (HC) and patients with Alzheimer’s disease (AD). Methods We obtained data from the National Alzheimer’s Coordinating Center (NIA/NIH Grant U24-AG072122). We built separate cognitive connectomes for DLB (n=104), HC (n= 3703), and AD (n=1985) groups using pairwise correlations between 24 cognitive variables mapping multiple cognitive functions. The cognitive connectomes in DLB, HC, and AD groups were compared using standard global and nodal graph measures of centrality, integration, and segregation. Results In global connectome measures, DLB patients showed a higher global efficiency (integration) and lower transitivity (segregation) than HCs and AD. Nodal connectome measures showed a higher global efficiency in most cognitive functions in DLB compared to HCs. Additionally, we found a lower local efficiency (segregation) and nodal strength (centrality) in memory variables and a higher participation coefficient in executive variables (centrality) in DLB compared with both HCs and AD. Conclusions The cognitive connectome in DLB showed a signature dedifferentiation pattern of aberrant correlations. Executive, processing speed and attention functions played a central role in the cognitive connectome of DLB patients. Furthermore, the role of executive and memory functions in the cognitive connectome distinguished DLB and AD patients. These findings may help advance our understanding of the clinical phenotype in DLB, and continue to improve the challenging differential diagnosis between DLB and AD.