Multimodal Brain Imaging Reveals Structural Differences in Alzheimer's Disease Polygenic Risk Carriers: A Study in Healthy Young Adults

Impact of genetic predisposition to late-onset neurodegenerative diseases on early life outcomes and brain structure

Most patients with late-onset neurodegenerative diseases such as Alzheimer's and Parkinson's have a complex aetiology resulting from numerous genetic risk variants of small effects located across the genome, environmental factors, and the interaction between genes and environment. Over the last decade, genome-wide association studies (GWAS) and post-GWAS analyses have shed light on the polygenic architecture of these diseases, enabling polygenic risk scores (PRS) to estimate an individual's relative genetic liability for presenting with the disease. PRS can screen and stratify individuals based on their genetic risk, potentially years or even decades before the onset of clinical symptoms. An emerging body of evidence from various research studies suggests that genetic susceptibility to late-onset neurodegenerative diseases might impact early life outcomes, including cognitive function, brain structure and function, and behaviour. This article summarises recent findings exploring the potential impact of genetic susceptibility to neurodegenerative diseases on early life outcomes. A better understanding of the impact of genetic susceptibility to neurodegenerative diseases early in life could be valuable in disease screening, detection, and prevention and in informing treatment strategies before significant neural damage has occurred. However, ongoing studies have limitations. Overall, our review found several studies focused on APOE haplotypes and Alzheimer's risk, but a limited number of studies leveraging polygenic risk scores or focused on genetic susceptibility to other late-onset conditions.

Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants

INTRODUCTION

We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults.

METHODS

Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume.

RESULTS

AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices.

DISCUSSION

APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Proof-of-concept recall-by-genotype study of extremely low and high Alzheimer's polygenic risk reveals autobiographical deficits and cingulate cortex correlates

BACKGROUND

Genome-wide association studies demonstrate that Alzheimer's disease (AD) has a highly polygenic architecture, where thousands of independent genetic variants explain risk with high classification accuracy. This AD polygenic risk score (AD-PRS) has been previously linked to preclinical cognitive and neuroimaging features observed in asymptomatic individuals. However, shared variance between AD-PRS and neurocognitive features are small, suggesting limited preclinical utility.

METHODS

Here, we recruited sixteen clinically asymptomatic individuals (mean age 67; range 58-76) with either extremely low / high AD-PRS (defined as at least 2 standard deviations from the wider sample mean (N = 4504; N EFFECTIVE = 90)) with comparable age sex and education level. We assessed group differences in autobiographical memory and T1-weighted structural neuroimaging features.

RESULTS

We observed marked reductions in autobiographical recollection (Cohen's d =  - 1.66; P FDR = 0.014) and midline structure (cingulate) thickness (Cohen's d =  - 1.55, P FDR = 0.05), with no difference in hippocampal volume (P > 0.3). We further confirm the negative association between AD-PRS and cingulate thickness in a larger study with a comparable age (N = 31,966, β =  - 0.002, P = 0.011), supporting the validity of our approach.

CONCLUSIONS

These observations conform with multiple streams of prior evidence suggesting alterations in cingulate structures may occur in individuals with higher AD genetic risk. We were able to use a genetically informed research design strategy that significantly improved the efficiency and power of the study. Thus, we further demonstrate that the recall-by-genotype of AD-PRS from wider samples is a promising approach for the detection, assessment, and intervention in specific individuals with increased AD genetic risk.

NMR-based metabolomics in Alzheimer's disease research: a review

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the most common cause of dementia in the elderly population worldwide. Currently, there is no cure for AD, and the continuous increase in the number of susceptible individuals poses one of the most significant emerging threats to public health. However, the molecular pathways involved in the onset and progression of AD are not fully understood. This information is crucial for developing less invasive diagnostic instruments and discovering novel potential therapeutic targets. Metabolomics studies the complete ensemble of endogenous and exogenous metabolites present in biological specimens and may provide an interesting approach to identify alterations in multiple biochemical processes associated with AD onset and evolution. In this mini review, we summarize the results from metabolomic studies conducted using nuclear magnetic resonance (NMR) spectroscopy on human biological samples (blood derivatives, cerebrospinal fluid, urine, saliva, and tissues) from AD patients. We describe the metabolic alterations identified in AD patients compared to controls and to patients diagnosed with mild cognitive impairment (MCI). Moreover, we discuss the challenges and issues associated with the application of NMR-based metabolomics in the context of AD research.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

BACKGROUND

Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical.

METHODS

Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination).

RESULTS

Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone.

CONCLUSION

Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

Classification of Alzheimer's disease based on hippocampal multivariate morphometry statistics

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline, and mild cognitive impairment (MCI) is associated with a high risk of developing AD. Hippocampal morphometry analysis is believed to be the most robust magnetic resonance imaging (MRI) markers for AD and MCI. Multivariate morphometry statistics (MMS), a quantitative method of surface deformations analysis, is confirmed to have strong statistical power for evaluating hippocampus.

AIMS

We aimed to test whether surface deformation features in hippocampus can be employed for early classification of AD, MCI, and healthy controls (HC).

METHODS

We first explored the differences in hippocampus surface deformation among these three groups by using MMS analysis. Additionally, the hippocampal MMS features of selective patches and support vector machine (SVM) were used for the binary classification and triple classification.

RESULTS

By the results, we identified significant hippocampal deformation among the three groups, especially in hippocampal CA1. In addition, the binary classification of AD/HC, MCI/HC, AD/MCI showed good performances, and area under curve (AUC) of triple-classification model achieved 0.85. Finally, positive correlations were found between the hippocampus MMS features and cognitive performances.

CONCLUSIONS

The study revealed significant hippocampal deformation among AD, MCI, and HC. Additionally, we confirmed that hippocampal MMS can be used as a sensitive imaging biomarker for the early diagnosis of AD at the individual level.

Pathway-specific polygenic scores for Alzheimer's disease are associated with changes in brain structure in younger and older adults

Genome-wide association studies have identified multiple Alzheimer's disease risk loci with small effect sizes. Polygenic risk scores, which aggregate these variants, are associated with grey matter structural changes. However, genome-wide scores do not allow mechanistic interpretations. The present study explored associations between disease pathway-specific scores and grey matter structure in younger and older adults. Data from two separate population cohorts were used as follows: the Avon Longitudinal Study of Parents and Children, mean age 19.8, and UK Biobank, mean age 64.4 (combined n = 18 689). Alzheimer's polygenic risk scores were computed using the largest genome-wide association study of clinically assessed Alzheimer's to date. Relationships between subcortical volumes and cortical thickness, pathway-specific scores and genome-wide scores were examined. Increased pathway-specific scores were associated with reduced cortical thickness in both the younger and older cohorts. For example, the reverse cholesterol transport pathway score showed evidence of association with lower left middle temporal cortex thickness in the younger Avon participants (P = 0.034; beta = -0.013, CI -0.025, -0.001) and in the older UK Biobank participants (P = 0.019; beta = -0.003, CI -0.005, -4.56 × 10-4). Pathway scores were associated with smaller subcortical volumes, such as smaller hippocampal volume, in UK Biobank older adults. There was also evidence of positive association between subcortical volumes in Avon younger adults. For example, the tau protein-binding pathway score was negatively associated with left hippocampal volume in UK Biobank (P = 8.35 × 10-05; beta = -11.392, CI -17.066, -5.718) and positively associated with hippocampal volume in the Avon study (P = 0.040; beta = 51.952, CI 2.445, 101.460). The immune response score had a distinct pattern of association, being only associated with reduced thickness in the right posterior cingulate in older and younger adults (P = 0.011; beta = -0.003, CI -0.005, -0.001 in UK Biobank; P = 0.034; beta = -0.016, CI -0.031, -0.001 in the Avon study). The immune response score was associated with smaller subcortical volumes in the older adults, but not younger adults. The disease pathway scores showed greater evidence of association with imaging phenotypes than the genome-wide score. This suggests that pathway-specific polygenic methods may allow progress towards a mechanistic understanding of structural changes linked to polygenic risk in pre-clinical Alzheimer's disease. Pathway-specific profiling could further define pathophysiology in individuals, moving towards precision medicine in Alzheimer's disease.

Association between polygenic risk for Alzheimer's disease and brain structure in children and adults

BACKGROUND

The correlations between genetic risk for Alzheimer's disease (AD) with comprehensive brain regions at a regional scale are still not well understood. We aim to explore whether these associations vary across different age stages.

METHODS

This study used large existing genome-wide association datasets to calculate polygenic risk score (PRS) for AD in two populations from the UK Biobank (N ~ 23 000) and Adolescent Brain Cognitive Development Study (N ~ 4660) who had multimodal macrostructural and microstructural magnetic resonance imaging (MRI) metrics. We used linear mixed-effect models to assess the strength of the association between AD PRS and multiple MRI metrics of regional brain structures at different stages of life.

RESULTS

Compared to those with lower PRSs, adolescents with higher PRSs had thinner cortex in the caudal anterior cingulate and supramarginal. In the middle-aged and elderly population, AD PRS had correlations with regional structure shrink primarily located in the cingulate, prefrontal cortex, hippocampus, thalamus, amygdala, and striatum, whereas the brain expansion was concentrated near the occipital lobe. Furthermore, both adults and adolescents with higher PRSs exhibited widespread white matter microstructural changes, indicated by decreased fractional anisotropy (FA) or increased mean diffusivity (MD).

CONCLUSIONS

In conclusion, our results suggest genetic loading for AD may influence brain structures in a highly dynamic manner, with dramatically different patterns at different ages. This age-specific change is consistent with the classical pattern of brain impairment observed in AD patients.

APOE ɛ4, but not polygenic Alzheimer's disease risk, is related to longitudinal decrease in hippocampal brain activity in non-demented individuals

The hippocampus is affected early in Alzheimer's disease (AD) and altered hippocampal functioning influences normal cognitive aging. Here, we used task-based functional MRI to assess if the APOE ɛ4 allele or a polygenic risk score (PRS) for AD was linked to longitudinal changes in memory-related hippocampal activation in normal aging (baseline age 50-95, n = 292; n = 182 at 4 years follow-up, subsequently non-demented for at least 2 years). Mixed-models were used to predict level and change in hippocampal activation by APOE ɛ4 status and PRS based on gene variants previously linked to AD at p ≤ 1, p < 0.05, or p < 5e-8 (excluding APOE). APOE ɛ4 and PRS_p<5e-8 significantly predicted AD risk in a larger sample from the same study population (n = 1542), while PRS_p≤1 predicted memory decline. APOE ɛ4 was linked to decreased hippocampal activation over time, with the most prominent effect in the posterior hippocampi, while PRS was unrelated to hippocampal activation at all p-thresholds. These results suggests a link for APOE ɛ4, but not for AD genetics in general, on functional changes of the hippocampi in normal aging.

Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife

We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD-GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle-aged participants (311 with brain MRI). A higher AD-GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (-0.14 standard deviation [SD] [95% confidence interval {CI}: -0.26, -0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE ε4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629-634.

Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population

Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.

Improved Prediction of Amyloid-β and Tau Burden Using Hippocampal Surface Multivariate Morphometry Statistics and Sparse Coding

BACKGROUND

Amyloid-β (Aβ) plaques and tau protein tangles in the brain are the defining 'A' and 'T' hallmarks of Alzheimer's disease (AD), and together with structural atrophy detectable on brain magnetic resonance imaging (MRI) scans as one of the neurodegenerative ('N') biomarkers comprise the "ATN framework" of AD. Current methods to detect Aβ/tau pathology include cerebrospinal fluid (invasive), positron emission tomography (PET; costly and not widely available), and blood-based biomarkers (promising but mainly still in development).

OBJECTIVE

To develop a non-invasive and widely available structural MRI-based framework to quantitatively predict the amyloid and tau measurements.

METHODS

With MRI-based hippocampal multivariate morphometry statistics (MMS) features, we apply our Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) method combined with the ridge regression model to individual amyloid/tau measure prediction.

RESULTS

We evaluate our framework on amyloid PET/MRI and tau PET/MRI datasets from the Alzheimer's Disease Neuroimaging Initiative. Each subject has one pair consisting of a PET image and MRI scan, collected at about the same time. Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics.

CONCLUSION

The MMS-based PASCP-MP is an efficient tool that can bridge hippocampal atrophy with amyloid and tau pathology and thus help assess disease burden, progression, and treatment effects.

Air pollution exposure during pregnancy and childhood, APOE ε4 status and Alzheimer polygenic risk score, and brain structural morphology in preadolescents

BACKGROUND

Air pollution exposure is associated with impaired neurodevelopment, altered structural brain morphology in children, and neurodegenerative disorders. Differential susceptibility to air pollution may be influenced by genetic features.

OBJECTIVES

To evaluate whether the apolipoprotein E (APOE) genotype or the polygenic risk score (PRS) for Alzheimer's Disease (AD) modify the association between air pollution exposure during pregnancy and childhood and structural brain morphology in preadolescents.

METHODS

We included 1186 children from the Generation R Study. Concentrations of fourteen air pollutants were calculated at participants' home addresses during pregnancy and childhood using land-use-regression models. Structural brain images were collected at age 9-12 years to assess cortical and subcortical brain volumes. APOE status and PRS for AD were examined as genetic modifiers. Linear regression models were used to conduct single-pollutant and multi-pollutant (using the Deletion/Substitution/Addition algorithm) analyses with a two-way interaction between air pollution and each genetic modifier.

RESULTS

Higher pregnancy coarse particulate matter (PM_coarse) and childhood polycyclic aromatic hydrocarbons exposure was differentially associated with larger cerebral white matter volume in APOE ε4 carriers compared to non-carriers (29,485 mm³ (95% CI 6,189; 52,781) and 18,663 mm³ (469; 36,856), respectively). Higher pregnancy PM_coarse exposure was differentially associated with larger cortical grey matter volume in children with higher compared to lower PRS for AD (19436 mm³ (825, 38,046)).

DISCUSSION

APOE status and PRS for AD possibly modify the association between air pollution exposure and brain structural morphology in preadolescents. Higher air pollution exposure is associated with larger cortical volumes in APOE ε4 carriers and children with a high PRS for AD. This is in line with typical brain development, suggesting an antagonistic pleiotropic effect of these genetic features (i.e., protective effect in early-life, but neurodegenerative effect in adulthood). However, we cannot discard chance findings. Future studies should evaluate trajectorial brain development using a longitudinal design.

Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study

The parahippocampal cingulum bundle (PHCB) interconnects regions known to be vulnerable to early Alzheimer's disease (AD) pathology, including posteromedial cortex and medial temporal lobe. While AD-related pathology has been robustly associated with alterations in PHCB microstructure, specifically lower fractional anisotropy (FA) and higher mean diffusivity (MD), emerging evidence indicates that the reverse pattern is evident in younger adults at increased risk of AD. In one such study, Hodgetts et al. (2019) reported that healthy young adult carriers of the apolipoprotein-E (APOE) ε4 allele - the strongest common genetic risk factor for AD - showed higher FA and lower MD in the PHCB but not the inferior longitudinal fasciculus (ILF). These results are consistent with proposals claiming that heightened neural activity and intrinsic connectivity play a significant role in increasing posteromedial cortex vulnerability to amyloid-β and tau spread beyond the medial temporal lobe. Given the implications for understanding AD risk, here we sought to replicate Hodgetts et al.'s finding in a larger sample (N = 128; 40 APOE ε4 carriers, 88 APOE ε4 non-carriers) of young adults (age range = 19-33). Extending this work, we also conducted an exploratory analysis using a more advanced measure of white matter microstructure: hindrance modulated orientational anisotropy (HMOA). Contrary to the original study, we did not observe higher FA or lower MD in the PHCB of APOE ε4 carriers relative to non-carriers. Bayes factors (BFs) further revealed moderate-to-strong evidence in support of these null findings. In addition, we observed no APOE ε4-related differences in PHCB HMOA. Our findings indicate that young adult APOE ε4 carriers and non-carriers do not differ in PHCB microstructure, casting some doubt on the notion that early-life variation in PHCB tract microstructure might enhance vulnerability to amyloid-β accumulation and/or tau spread.

The impact of genetic risk for Alzheimer's disease on the structural brain networks of young adults

Introduction

We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children.

Methods

Diffusion MRI data were used to perform whole-brain tractography and generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant's genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and (a) the graph theoretical metrics of the structural networks and (b) the rich-club, feeder and local connectivity of the whole-brain networks.

Results

In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.19, p = 1.4 × 10-3), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r = 0.16, p = 5.5 × 10-3), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (r = -0.16, p = 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.14, p = 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r = -0.16, p = 0.035; r = -0.15, p = 0.036).

Discussion

We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.

Effects of age on the hippocampus and verbal memory in adults with autism spectrum disorder: Longitudinal versus cross-sectional findings

Research studying aging in adults with autism spectrum disorder (ASD) is growing, but longitudinal work is needed. Autistic adults have increased risk of dementia, altered hippocampal volumes and fornix integrity, and verbal memory difficulties compared with neurotypical (NT) adults. This study examined longitudinal aging in middle-age adults with ASD versus a matched NT group, and compared findings with cross-sectional age effects across a broad adult age range. Participants were 194 adults with (n = 106; 74 male) and without (n = 88; 52 male) ASD, ages 18-71. Participants (n = 45; 40-70 age range) with two visits (2-3 years apart) were included in a longitudinal analysis. Hippocampal volume, fornix fractional anisotropy (FA), and verbal memory were measured via T1-weighted MRI, diffusion tensor imaging, and the Rey Auditory Verbal Learning Test, respectively. Longitudinal mixed models were used for hippocampal system variables and reliable change index categories were used for Auditory Verbal Learning Test analyses. Multivariate regression was used for cross-sectional analyses. Middle-age adults with ASD had greater longitudinal hippocampal volume loss and were more likely to show clinically meaningful decline in short-term memory, compared with NT. In contrast, cross-sectional associations between increasing age and worsening short-term memory were identified in NT, but not autistic adults. Reduced fornix FA and long-term memory in ASD were found across the broad cross-sectional age range. These preliminary longitudinal findings suggest accelerated hippocampal volume loss in ASD and slightly higher rates of clinically-meaningful decline in verbal short-term memory. Contradictory cross-sectional and longitudinal results underscore the importance of longitudinal aging research in autistic adults. LAY SUMMARY: Autistic adults have increased risk of dementia, differences in brain memory structures, and difficulty with memory compared with neurotypical (NT) adults. However, there are no publications that follow the same middle-age autistic adults over time to see how their brain and memory change. Our preliminary findings in a small middle-age autism sample suggest a key memory brain structure, the hippocampus, may shrink faster over 2-3 years compared with NT, and short-term memory may become more challenging for some. Across a broad adult range, autistic adults also had reduced integrity of connections to the hippocampus and greater challenges with long-term memory. In our larger sample across a broad age range, the results did not hint at this aforementioned pattern of accelerated aging. This underscores the importance of more aging research in autism, and especially research where people are followed over time.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Alzheimer’s Disease Polygenic Risk Score Is Not Associated With Cognitive Decline Among Older Adults With Type 2 Diabetes

Objectives

Multiple risk loci for late-onset Alzheimer’s disease (LOAD) have been identified. Type 2 diabetes (T2D) is a risk factor for cognitive decline, dementia and Alzheimer’s disease (AD). We investigated the association of polygenic risk score (PRS) for LOAD with overall cognitive functioning and longitudinal decline, among older adults with T2D.

Methods

The study included 1046 Jewish participants from the Israel Diabetes and Cognitive Decline (IDCD) study, aged ≥ 65 years, diagnosed with T2D, and cognitively normal at baseline. The PRS included variants from 26 LOAD associated loci (at genome-wide significance level), and was calculated with and without APOE. Outcome measures, assessed in 18 months intervals, were global cognition and the specific domains of episodic memory, attention/working memory, executive functions, and language/semantic categorization. Random coefficient models were used for analysis, adjusting for demographic variables, T2D-related characteristics, and cardiovascular factors. Additionally, in a subsample of 202 individuals, we analyzed the association of PRS with the volumes of total gray matter, frontal lobe, hippocampus, amygdala, and white matter hyperintensities. Last, the association of PRS with amyloid beta (Aβ) burden was examined in 44 participants who underwent an 18F-flutemetamol PET scan.

Results

The PRS was not significantly associated with overall functioning or decline in global cognition or any of the specific cognitive domains. Similarly, following correction for multiple testing, there was no association with Aβ burden and other brain imaging phenotypes.

Conclusion

Our results suggest that the cumulative effect of LOAD susceptibility loci is not associated with a greater rate of cognitive decline in older adults with T2D, and other pathways may underlie this link.

Polygenic score for Alzheimer’s disease identifies differential atrophy in hippocampal subfield volumes

Hippocampal subfield atrophy is a prime structural change in the brain, associated with cognitive aging and neurodegenerative diseases such as Alzheimer’s disease. Recent developments in genome-wide association studies (GWAS) have identified genetic loci that characterize the risk of hippocampal volume loss based on the processes of normal and abnormal aging. Polygenic risk scores are the genetic proxies mimicking the genetic role of the pre-existing vulnerabilities of the underlying mechanisms influencing these changes. Discriminating the genetic predispositions of hippocampal subfield atrophy between cognitive aging and neurodegenerative diseases will be helpful in understanding the disease etiology. In this study, we evaluated the polygenic risk of Alzheimer’s disease (AD PGRS) for hippocampal subfield atrophy in 1,086 individuals (319 cognitively normal (CN), 591 mild cognitively impaired (MCI), and 176 Alzheimer’s disease dementia (ADD)). Our results showed a stronger association of AD PGRS effect on the left hemisphere than on the right hemisphere for all the hippocampal subfield volumes in a mixed clinical population (CN+MCI+ADD). The subfields CA1, CA4, hippocampal tail, subiculum, presubiculum, molecular layer, GC-ML-DG, and HATA showed stronger AD PGRS associations with the MCI+ADD group than with the CN group. The subfields CA3, parasubiculum, and fimbria showed moderately higher AD PGRS associations with the MCI+ADD group than with the CN group. Our findings suggest that the eight subfield regions, which were strongly associated with AD PGRS are likely involved in the early stage ADD and a specific focus on the left hemisphere could enhance the early prediction of ADD.

Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Anti-LINGO-1 antibody treatment alleviates cognitive deficits and promotes maturation of oligodendrocytes in the hippocampus of APP/PS1 mice

Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein 1 (LINGO-1), a negative regulator of oligodendrocyte differentiation and myelination, is associated with cognitive function, and its expression is highly upregulated in Alzheimer's disease (AD) patients. Anti-LINGO-1 antibody treatment can effectively antagonize the negative regulatory effect of LINGO-1. In this study, we aim to assess the effect of anti-LINGO-1 antibody treatment on cognition and hippocampal oligodendrocytes in an AD transgenic animal model. First, 10-month-old male APP/PS1 mice were administered anti-LINGO-1 antibody for 8 weeks. Then, learning and memory abilities were assessed with the Morris water maze (MWM) and Y-maze tests, and amyloid-beta (Aβ) deposition and hippocampal oligodendrocytes were investigated by immunohistochemistry, immunofluorescence, and stereology. We found that anti-LINGO-1 antibody alleviated the deficits in spatial learning and memory abilities and working and reference memory abilities, decreased the density of LINGO-1 positive cells, decreased Aβ deposition, significantly increased the number of mature oligodendrocytes and the density of myelin, reversed the abnormal increases in the number of oligodendrocyte lineage cells and the densities of oligodendrocytes precursor cells in APP/PS1 mice. Our results provide evidence that LINGO-1 might be involved in the process of oligodendrocyte dysmaturity in the hippocampus of AD mice and that antagonizing LINGO-1 can alleviate cognitive deficits in APP/PS1 mice and decrease Aβ deposition and promote oligodendrocyte differentiation and maturation in the hippocampus of these mice. Our findings suggest that changes in LINGO-1 and oligodendrocytes in the hippocampus play important roles in the pathogenesis of AD and that antagonizing LINGO-1 might be a potential therapeutic strategy for AD. This article is protected by copyright. All rights reserved.

Genomic studies across the lifespan point to early mechanisms determining subcortical volumes

BACKGROUND

Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration.

METHODS

Using large population-based brain imaging datasets across the lifespan (N<40,628) we aimed to: (i) estimate the heritability of subcortical volumes in young (18-35), middle (35-65), and older age (65+), and their genetic correlation across age groups; (ii) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; (iii) explore their association with neurological phenotypes.

RESULTS

Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, ten loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age-groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically-predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age.

CONCLUSIONS

Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.

Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases

Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that magnetic resonance imaging (MRI)-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain Aβ burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) [Accuracy (ACC) = 0.89 (ADNI)] and in cognitively unimpaired (CU) individuals [ACC = 0.79 (ADNI) and ACC = 0.81 (OASIS)]. These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.

Functional co-activation of the default mode network in APOE ε4-carriers: A replication study

Structural and functional alterations of the brain in persons genetically at-risk for Alzheimer's disease (AD) are crucial in unravelling AD development. Filippini et al. found that the default mode network (DMN) is already affected in young APOE ε4-carriers, with increased co-activation of the DMN during rest and increased hippocampal task activation. We aimed to replicate the early findings of Filippini et al, using the APOE gene, still the principal AD risk gene, and extended this with a polygenic risk score (PRS) analysis for AD, using the Human Connectome Project dataset (HCP). We included participants from the HCP S1200 dataset (age range: 22-36 years). We studied morphometric features, functional DMN co-activation and functional task activation of recollection performance. Permutation Analysis of Linear Models (PALM) was used to test for group differences between APOE ε4-carriers and non-carriers, and to test the association with PRS. PALM controls for biases induced by the family structure of the HCP sample. Results were family-wise error rate corrected at p < 0.05. Our primary analysis did not replicate the early findings of Filippini et al. (2009). However, compared with non-carriers, APOE ε4-carriers showed increased functional activation during the encoding of subsequently recollected items in areas related to facial recognition (p<0.05, t>756.11). This increased functional activation was also positively associated with PRS (APOE variants included) (p<0.05, t>647.55). Our results are supportive for none to limited genetic effects on brain structure and function in young adults. Taking the methodological considerations of replication studies into account, the true effect of APOE ε4-carriership is likely smaller than indicated in the Filippini paper. However, it still holds that we may not yet be able to detect already present measurable effects decades before a clinical expression of AD. Since the mechanistic pathway of AD is likely to encompass many different factors, further research should be focused on the interactions of genetic risk, biomarkers, aging and lifestyle factors over the life course. Sensitive functional neuroimaging as used here may help disentangling these complex interactions.

Pathway-Specific Genetic Risk for Alzheimer's Disease Differentiates Regional Patterns of Cortical Atrophy in Older Adults

Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic factors may influence both aging and disease. Here we focused on this issue and investigated effects of multiple genetic loci previously identified to be associated with late-onset Alzheimer's disease (AD) on brain structure of older adults from a population sample. We calculated a genetic risk score (GRS) using genome-wide significant single-nucleotide polymorphisms from genome-wide association studies of AD and tested its effect on cortical thickness (CT). We observed a common pattern of cortical thinning (right inferior frontal, left posterior temporal, medial occipital cortex). To identify CT changes by specific biological processes, we subdivided the GRS effect according to AD-associated pathways and performed follow-up analyses. The common pattern from the main analysis was further differentiated by pathway-specific effects yielding a more bilateral pattern. Further findings were located in the superior parietal and mid/anterior cingulate regions representing 2 unique pathway-specific patterns. All patterns, except the superior parietal pattern, were influenced by apolipoprotein E. Our step-wise approach revealed atrophy patterns that partially resembled imaging findings in early stages of AD. Our study provides evidence that genetic burden for AD contributes to structural brain variability in normal aging.

Alzheimer's disease genetic risk and sleep phenotypes in healthy young men: association with more slow waves and daytime sleepiness

STUDY OBJECTIVES

Sleep disturbances and genetic variants have been identified as risk factors for Alzheimer's disease (AD). Our goal was to assess whether genome-wide polygenic risk scores (PRS) for AD associate with sleep phenotypes in young adults, decades before typical AD symptom onset.

METHODS

We computed whole-genome PRS for AD and extensively phenotyped sleep under different sleep conditions, including baseline sleep, recovery sleep following sleep deprivation, and extended sleep opportunity, in a carefully selected homogenous sample of 363 healthy young men (22.1 years ± 2.7) devoid of sleep and cognitive disorders.

RESULTS

AD PRS was associated with more slow-wave energy, that is, the cumulated power in the 0.5-4 Hz EEG band, a marker of sleep need, during habitual sleep and following sleep loss, and potentially with larger slow-wave sleep rebound following sleep deprivation. Furthermore, higher AD PRS was correlated with higher habitual daytime sleepiness.

CONCLUSIONS

These results imply that sleep features may be associated with AD liability in young adults, when current AD biomarkers are typically negative, and support the notion that quantifying sleep alterations may be useful in assessing the risk for developing AD.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

A prospective cohort study of prodromal Alzheimer's disease: Prospective Imaging Study of Ageing: Genes, Brain and Behaviour (PISA)

This prospective cohort study, "Prospective Imaging Study of Ageing: Genes, Brain and Behaviour" (PISA) seeks to characterise the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). In particular, we are recruiting midlife and older Australians with high and low genetic risk of dementia to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of disease onset. PISA utilises genetic prediction to recruit and enrich a prospective cohort and follow them longitudinally. Online surveys and cognitive testing are used to characterise an Australia-wide sample currently totalling over 3800 participants. Participants from a defined at-risk cohort and positive controls (clinical cohort of patients with mild cognitive impairment or early AD) are invited for onsite visits for detailed functional, structural and molecular neuroimaging, lifestyle monitoring, detailed neurocognitive testing, plus blood sample donation. This paper describes recruitment of the PISA cohort, study methodology and baseline demographics.

Associations between Alzheimer's disease polygenic risk scores and hippocampal subfield volumes in 17,161 UK Biobank participants

Hippocampal volume is an important biomarker of Alzheimer's disease (AD), and genetic risk of AD is associated with hippocampal atrophy. However, the hippocampus is not a uniform structure and has a number of subfields, the associations of which with age, sex, and polygenic risk score for AD (PRS_AD) have been inadequately investigated. We examined these associations in 17,161 cognitively normal UK Biobank participants (44-80 years). Age was negatively associated with all the hippocampal subfield volumes and females had smaller volumes than men. Higher PRS_AD was associated with lower volumes in the bilateral whole hippocampus, hippocampal-amygdala-transition-area, and hippocampal tail; right subiculum; left cornu ammonis 1, cornu ammonis 4, molecular layer, and granule cell layer of dentate gyrus. Older individuals (median age 63 years, n = 8984) showed greater subfield vulnerability to high PRS_AD compared to the younger group (n = 8177), but the effect did not differ by sex. The pattern of subfield involvement in relation to the PRS_AD in community dwelling healthy individuals sheds additional light on the pathogenesis of AD.

Multimodal hippocampal and amygdala subfield volumetry in polygenic risk for Alzheimer's disease

Preclinical models of Alzheimer's disease (AD) suggest that volumetric reductions in medial temporal lobe (MTL) structures manifest before clinical onset. AD polygenic risk scores (PRSs) are further linked to reduced MTL volumes (the hippocampus/amygdala); however, the relationship between the PRS and specific subregions remains unclear. We determine the relationship between the AD-PRSs and MTL subregions in a large sample of young participants (N = 730, aged 22–35 years) using a multimodal (T1w/T2w) approach. We first demonstrate that the PRSs for the hippocampus/amygdala predict their respective volumes and specific hippocampal subregions (pFDR < 0.05). We further observe negative relationships between the AD-PRSs and whole hippocampal/amygdala volumes. Critically, we demonstrate novel associations between the AD-PRSs and specific hippocampal subfields such as CA1 (β = −0.096, pFDR = 0.045) and the fissure (β = −0.101, pFDR = 0.041). We provide evidence that the AD-PRS is linked to specific MTL subfields decades before AD onset. This may help inform preclinical models of AD risk, providing additional specificity for intervention and further insight into mechanisms by which common AD variants confer susceptibility.

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Polygenic risk for Alzheimer's disease (AD-PRS) explains significant proportion of AD.

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AD-PRS also linked to hippocampus and amygdala volume.

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AD-PRS is negatively associated with specific hippocampal subfields.

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Polygenic AD models help us understand genetic contributions to medial temporal lobe nuclei.

Genetic risk for Alzheimer disease predicts hippocampal volume through the human lifespan

Objective

To test the hypothesis that genetic risk for Alzheimer disease (AD) may represent a stable influence on the brain from early in life, rather than being primarily age dependent, we investigated in a lifespan sample of 1,181 persons with a total of 2,690 brain scans, whether higher polygenic risk score (PGS) for AD and presence of APOE ε4 was associated with lower hippocampal volumes to begin with, as an offset effect, or possibly faster decline in older age.

Methods

Using general additive mixed models, we assessed the relations of PGS for AD, including variants in APOE with hippocampal volume and its change in a cognitively healthy longitudinal lifespan sample (age range: 4–95 years, mean visit age 39.7 years, SD 26.9 years), followed for up to 11 years.

Results

AD-PGS and APOE ε4 in isolation showed a significant negative effect on hippocampal volume. The effect of a 1 sample SD increase in AD-PGS on hippocampal volume was estimated to –36.4 mm³ (confidence interval [CI]: –71.8, –1.04) and the effect of carrying ε4 allele(s) –107.0 mm³ (CI: –182.0, –31.5). Offset effects of AD-PGS and APOE ε4 were present in hippocampal development, and interactions between age and genetic risk on volume change were not consistently observed.

Conclusions

Endophenotypic manifestation of polygenic risk for AD may be seen across the lifespan in cognitively healthy persons, not being confined to clinical populations or older age. This emphasizes that a broader population and age range may be relevant targets for attempts to prevent AD.

Imaging Alzheimer's genetic risk using diffusion MRI: A systematic review

Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to investigate changes in white matter microstructure in Alzheimer's Disease. This paper aims to systematically review studies that examined the effect of Alzheimer's risk genes on white matter microstructure. We assimilated findings from 37 studies and reviewed their diffusion pre-processing and analysis methods. Most studies estimate the diffusion tensor (DT) and compare derived quantitative measures such as fractional anisotropy and mean diffusivity between groups. Those with increased AD genetic risk are associated with reduced anisotropy and increased diffusivity across the brain, most notably the temporal and frontal lobes, cingulum and corpus callosum. Structural abnormalities are most evident amongst those with established Alzheimer's Disease. Recent studies employ signal representations and analysis frameworks beyond DT MRI but show that dMRI overall lacks specificity to disease pathology. However, as the field advances, these techniques may prove useful in pre-symptomatic diagnosis or staging of Alzheimer's disease.

Independent and reproducible hippocampal radiomic biomarkers for multisite Alzheimer's disease: diagnosis, longitudinal progress and biological basis

Hippocampal morphological change is one of the main hallmarks of Alzheimer's disease (AD). However, whether hippocampal radiomic features are robust as predictors of progression from mild cognitive impairment (MCI) to AD dementia and whether these features provide any neurobiological foundation remains unclear. The primary aim of this study was to verify whether hippocampal radiomic features can serve as robust magnetic resonance imaging (MRI) markers for AD. Multivariate classifier-based support vector machine (SVM) analysis provided individual-level predictions for distinguishing AD patients (n = 261) from normal controls (NCs; n = 231) with an accuracy of 88.21% and intersite cross-validation. Further analyses of a large, independent the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 1228) reinforced these findings. In MCI groups, a systemic analysis demonstrated that the identified features were significantly associated with clinical features (e.g., apolipoprotein E (APOE) genotype, polygenic risk scores, cerebrospinal fluid (CSF) Aβ, CSF Tau), and longitudinal changes in cognition ability; more importantly, the radiomic features had a consistently altered pattern with changes in the MMSE scores over 5 years of follow-up. These comprehensive results suggest that hippocampal radiomic features can serve as robust biomarkers for clinical application in AD/MCI, and further provide evidence for predicting whether an MCI subject would convert to AD based on the radiomics of the hippocampus. The results of this study are expected to have a substantial impact on the early diagnosis of AD/MCI.

Neural correlates of polygenic risk score for autism spectrum disorders in general population

Autism spectrum disorder is a highly prevalent and highly heritable neurodevelopmental condition, but studies have mostly taken traditional categorical diagnosis approach (yes/no for autism spectrum disorder). In contrast, an emerging notion suggests a continuum model of autism spectrum disorder with a normal distribution of autistic tendencies in the general population, where a full diagnosis is at the severe tail of the distribution. We set out to investigate such a viewpoint by investigating the interaction of polygenic risk scores for autism spectrum disorder and Age² on neuroimaging measures (cortical thickness and white matter connectivity) in a general population (n = 391, with age ranging from 3 to 21 years from the Pediatric Imaging, Neurocognition and Genetics study). We observed that children with higher polygenic risk for autism spectrum disorder exhibited greater cortical thickness for a large age span starting from 3 years up to ∼14 years in several cortical regions localized in bilateral precentral gyri and the left hemispheric postcentral gyrus and precuneus. In an independent case–control dataset from the Autism Brain Imaging Data Exchange (n = 560), we observed a similar pattern: children with autism spectrum disorder exhibited greater cortical thickness starting from 6 years onwards till ∼14 years in wide-spread cortical regions including (the ones identified using the general population). We also observed statistically significant regional overlap between the two maps, suggesting that some of the cortical abnormalities associated with autism spectrum disorder overlapped with brain changes associated with genetic vulnerability for autism spectrum disorder in healthy individuals. Lastly, we observed that white matter connectivity between the frontal and parietal regions showed significant association with polygenic risk for autism spectrum disorder, indicating that not only the brain structure, but the white matter connectivity might also show a predisposition for the risk of autism spectrum disorder. Our findings showed that the fronto-parietal thickness and connectivity are dimensionally related to genetic risk for autism spectrum disorder in general population and are also part of the cortical abnormalities associated with autism spectrum disorder. This highlights the necessity of considering continuum models in studying the aetiology of autism spectrum disorder using polygenic risk scores and multimodal neuroimaging.

Polygenic risk for Alzheimer's disease shapes hippocampal scene-selectivity

Preclinical models of Alzheimer's disease (AD) suggest APOE modulates brain function in structures vulnerable to AD pathophysiology. However, genome-wide association studies now demonstrate that AD risk is shaped by a broader polygenic architecture, estimated via polygenic risk scoring (AD-PRS). Despite this breakthrough, the effect of AD-PRS on brain function in young individuals remains unknown. In a large sample (N = 608) of young, asymptomatic individuals, we measure the impact of both (i) APOE and (ii) AD-PRS on a vulnerable cortico-limbic scene-processing network heavily implicated in AD pathophysiology. Integrity of this network, which includes the hippocampus (HC), is fundamental for maintaining cognitive function during ageing. We show that AD-PRS, not APOE, selectively influences activity within the HC in response to scenes, while other perceptual nodes remained intact. This work highlights the impact of polygenic contributions to brain function beyond APOE, which could aid potential therapeutic/interventional strategies in the detection and prevention of AD.

The multiplex model of the genetics of Alzheimer's disease

Genes play a strong role in Alzheimer's disease (AD), with late-onset AD showing heritability of 58-79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.

Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory

It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N ​= ​1097) and the USA (N ​= ​723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R² ​= ​0.006 and 0.016 respectively, p ​< ​0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.

Genetic Burden for Late-Life Neurodegenerative Disease and Its Association With Early-Life Lipids, Brain, Behavior, and Cognition

BACKGROUND

Genetics play a significant role in the etiology of late-life neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. Part of the individual differences in risk for these diseases can be traced back decades before the onset of disease symptoms. Previous studies have shown evidence for plausible links of apolipoprotein E (APOE), the most important genetic marker for Alzheimer's disease, with early-life cognition and neuroimaging markers. We aimed to assess whether genome-wide genetic burden for the aforementioned neurodegenerative diseases plays a role in early-life processes.

METHODS

We studied children from the Generation R Study, a prospective birth cohort. APOE genotypes and polygenic genetic burdens for Alzheimer's disease, Parkinson's disease, and frontotemporal dementia were obtained through genome-wide genotyping. Non-verbal intelligence was assessed through cognitive tests at the research center around the age of 6 years, and educational attainment through a national school performance test around the age of 11 years. The Child Behavior Checklist was administered around the age of 10 years, and data from the anxious/depressed, withdrawn/depressed, and the internalizing behavior problems scales were used. Children participated in a neuroimaging study when they were 10 years old, in which structural brain metrics were obtained. Lipid serum profiles, which may be influenced by APOE genotype, were assessed from venal blood obtained around the age of 6 years. The sample size per analysis varied between 1,641 and 3,650 children due to completeness of data.

RESULTS

We did not find evidence that APOE genotype or the polygenic scores impact on childhood nonverbal intelligence, educational attainment, internalizing behavior, and global brain structural measures including total brain volume and whole brain fractional anisotropy (all p > 0.05). Carriership of the APOE ε2 allele was associated with lower and APOE ε4 with higher low-density lipoprotein cholesterol concentrations when compared to APOE ε3/ε3 carriers.

CONCLUSION

We found no evidence that genetic burden for late-life neurodegenerative diseases associates with early-life cognition, internalizing behavior, or global brain structure.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

The Radiogenomics of Late-onset Alzheimer Disease

Radiogenomics, defined as the integrated analysis of radiologic imaging and genetic data, is a well-established tool shown to augment neuroimaging in the clinical diagnosis, prognostication, and scientific study of late-onset Alzheimer disease (LOAD). Early work using candidate single nucleotide polymorphisms (SNPs) identified genetic variation in APOE, BIN1, CLU, and CR1 as key modifiers of brain structure and function using magnetic resonance imaging (MRI). More recently, polygenic risk scores used in conjunction with MRI and positron emission tomography have shown great promise as a risk-stratification tool for clinical trials and care-management decisions. In addition, recent work using multimodal MRI and positron emission tomography as proxies of LOAD progression has identified novel risk variants that are enhancing our understanding of LOAD pathophysiology and progression. Herein, we highlight key studies and trends in the radiogenomics of LOAD over the past two decades and their implications for clinical practice and scientific research.

Microglia - mediated immunity partly contributes to the genetic association between Alzheimer's disease and hippocampal volume

Genome-wide association studies (GWAS) suggest that Alzheimer's disease (AD) is partly explained by a burden of risk alleles (single nucleotide polymorphisms; SNPs) with relatively small effects. However, the mechanisms by which these loci cumulatively confer susceptibility remain largely unknown. Accumulating evidence suggests an association between increased AD risk allele burden (measured via a polygenic risk profile score; AD-RPS) with reduced hippocampal volume (HV) across a number of independent cohorts. These lines of research suggest that the reduced HV may be a causal mechanism of risk in the development of late-onset Alzheimer's disease (AD). However, as RPS assesses broad, cumulative genetic risk, little is known about the biological processes which may explain this observation. Here, we leverage GWAS data from i) 17,008 late onset AD cases & 37,154 controls and ii) hippocampal volume (N = 12,147; N = 9707) to explore putative pathways that may explain this association. We first demonstrate an association between whole genome AD-RPS and HV (PT < 0.5, Z = -2.07, P = 0.038), confirming previous associations. Second, we restrict our analysis to SNPs within AD genes within a microglia mediated immunity network (N_GENES = 56). A microglia AD-RPS was further associated with HV (PT < 0.01; Z = -2.152, P = 0.031). Last, using a competitive, permutation based approach, we show that the common variation within this candidate gene-set is associated with HV, controlling for SNP set-size (P = 0.024). Together, the observations suggest that the relationship between AD and HV is partially explained by genes within an AD-linked microglia mediated immunity network.

Associations between rare microglia-linked Alzheimer's disease risk variants and subcortical brain volumes in young individuals

Introduction

Recent exome sequencing studies have identified three novel risk variants associated with Alzheimer's disease (AD). However, the mechanisms by which these variants confer risk are largely unknown.

Methods

In the present study, the impact of these rare coding variants (in ABI3, PLCG2, and TREM2) on all subcortical volumes is determined in a large sample of young healthy individuals (N = 756–765; aged 22–35 years).

Results

After multiple testing correction (P_CORRECTED < .05), rare variants were associated with basal ganglia volumes (TREM2 and PLCG2 effects within the putamen and pallidum, respectively). Nominal associations between TREM2 and reduced hippocampal and thalamic volumes were also observed.

Discussion

Our observations suggest that rare variants in microglia-mediated immunity pathway may contribute to the subcortical alterations observed in AD cases. These observations provide further evidence that genetic risk for AD may influence the volume of subcortical volumes and increase AD risk in early life processes.

The Contribution of Genetic Factors to Cognitive Impairment and Dementia: Apolipoprotein E Gene, Gene Interactions, and Polygenic Risk

Alzheimer's disease (AD) is a progressive neurodegenerative disease. Although it has been studied for years, the pathogenesis of AD is still controversial. Genetic factors may play an important role in pathogenesis, with the apolipoprotein E (APOE) gene among the greatest risk factors for AD. In this review, we focus on the influence of genetic factors, including the APOE gene, the interaction between APOE and other genes, and the polygenic risk factors for cognitive function and dementia. The presence of the APOE ε4 allele is associated with increased AD risk and reduced age of AD onset. Accelerated cognitive decline and abnormal internal environment, structure, and function of the brain were also found in ε4 carriers. The effect of the APOE promoter on cognition and the brain was confirmed by some studies, but further investigation is still needed. We also describe the effects of the associations between APOE and other genetic risk factors on cognition and the brain that exhibit a complex gene⁻gene interaction, and we consider the importance of using a polygenic risk score to investigate the association between genetic variance and phenotype.

Applying surface-based hippocampal morphometry to study APOE-E4 allele dose effects in cognitively unimpaired subjects

Apolipoprotein E (APOE) e4 is the major genetic risk factor for late-onset Alzheimer's disease (AD). The dose-dependent impact of this allele on hippocampal volumes has been documented, but its influence on general hippocampal morphology in cognitively unimpaired individuals is still elusive. Capitalizing on the study of a large number of cognitively unimpaired late middle aged and older adults with two, one and no APOE-e4 alleles, the current study aims to characterize the ability of our automated surface-based hippocampal morphometry algorithm to distinguish between these three levels of genetic risk for AD and demonstrate its superiority to a commonly used hippocampal volume measurement. We examined the APOE-e4 dose effect on cross-sectional hippocampal morphology analysis in a magnetic resonance imaging (MRI) database of 117 cognitively unimpaired subjects aged between 50 and 85 years (mean = 57.4, SD = 6.3), including 36 heterozygotes (e3/e4), 37 homozygotes (e4/e4) and 44 non-carriers (e3/e3). The proposed automated framework includes hippocampal surface segmentation and reconstruction, higher-order hippocampal surface correspondence computation, and hippocampal surface deformation analysis with multivariate statistics. In our experiments, the surface-based method identified APOE-e4 dose effects on the left hippocampal morphology. Compared to the widely-used hippocampal volume measure, our hippocampal morphometry statistics showed greater statistical power by distinguishing cognitively unimpaired subjects with two, one, and no APOE-e4 alleles. Our findings mirrored previous studies showing that APOE-e4 has a dose effect on the acceleration of brain structure deformities. The results indicated that the proposed surface-based hippocampal morphometry measure is a potential preclinical AD imaging biomarker for cognitively unimpaired individuals.

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Applied surface-based hippocampal morphometry on cognitively unimpaired subjects.

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Our study identified APOE-e4 dose effects on cognitively unimpaired subjects.

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Surface-based hippocampal morphometry outperformed the hippocampal volume measure.

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Surface-based hippocampal morphometry may be a potential preclinical AD biomarker.

Use of an Alzheimer's disease polygenic risk score to identify mild cognitive impairment in adults in their 50s

Early identification of younger, non-demented adults at elevated risk for Alzheimer's disease (AD) is crucial because the pathological process begins decades before dementia onset. Toward that end, we showed that an AD polygenic risk score (PRS) could identify mild cognitive impairment (MCI) in adults who were only in their 50s. Participants were 1176 white, non-Hispanic community-dwelling men of European ancestry in the Vietnam Era Twin Study of Aging (VETSA): 7% with amnestic MCI (aMCI); 4% with non-amnestic MCI (naMCI). Mean age was 56 years, with 89% <60 years old. Diagnosis was based on the Jak-Bondi actuarial/neuropsychological approach. We tested six P-value thresholds (0.05-0.50) for single nucleotide polymorphisms included in the ADPRS. After controlling for non-independence of twins and non-MCI factors that can affect cognition, higher PRSs were associated with significantly greater odds of having aMCI than being cognitively normal (odds ratios (ORs) = 1.36-1.43 for thresholds P < 0.20-0.50). The highest OR for the upper vs. lower quartile of the ADPRS distribution was 3.22. ORs remained significant after accounting for APOE-related SNPs from the ADPRS or directly genotyped APOE. Diabetes was associated with significantly increased odds of having naMCI (ORs = 3.10-3.41 for thresholds P < 0.05-0.50), consistent with naMCI having more vascular/inflammation components than aMCI. Analysis of sensitivity, specificity, and negative and positive predictive values supported some potential of ADPRSs for selecting participants in clinical trials aimed at early intervention. With participants 15+ years younger than most MCI samples, these findings are promising with regard to efforts to more effectively treat or slow AD progression.

Polygenic impact of common genetic risk loci for Alzheimer's disease on cerebral blood flow in young individuals

Genome-wide association studies (GWAS) show that many common alleles confer risk for developing Alzheimer’s disease (AD). These risk loci may contribute to MRI alterations in young individuals, preceding the clinical manifestations of AD. Prior evidence identifies vascular dysregulation as the earliest marker of disease progression. However, it remains unclear whether cerebrovascular function (measured via grey-matter cerebral blood flow (gmCBF)) is altered in young individuals with increased AD genetic risk. We establish relationships between gmCBF with APOE and AD polygenic risk score in a young cohort (N = 75; aged: 19–32). Genetic risk was assessed via a) possessing at least one copy of the APOE ɛ4 allele and b) a polygenic risk score (AD-PRS) estimated from AD-GWAS. We observed a reduction in gmCBF in APOE ɛ4 carriers and a negative relationship between AD-PRS and gmCBF. We further found regional reductions in gmCBF in individuals with higher AD-PRS across the frontal cortex (P_FWE < 0.05). Our findings suggest that a larger burden of AD common genetic risk alleles is associated with attenuated cerebrovascular function, during young adulthood. These results suggest that cerebral vasculature is a mechanism by which AD risk alleles confer susceptibility.