Zvart Abaryan - Academia.edu (original) (raw)

Papers by Zvart Abaryan

Deep transfer learning of brain shape morphometry predicts Body Mass Index (BMI) in the UK Biobank

16th International Symposium on Medical Information Processing and Analysis

Prior studies show that obesity is associated with accelerated brain aging and specific patterns ... more Prior studies show that obesity is associated with accelerated brain aging and specific patterns of brain atrophy. Finerscale mapping of the effects of obesity on the brain would help to understand how it promotes or interacts with disease effects, but so far, the influence of the obesity on finer-scale maps of anatomy remains unclear. In this study, we propose a deep transfer learning network based on Optimal Mass Transport (OMTNet) to classify individuals with normal versus overweight/obese body mass index (BMI) using vertex-wise brain shape metrics extracted from structural MRI scans from the UK Biobank study. First, an area-preserving mapping was used to project 3D brain surface meshes onto 2D planar meshes. Vertex-wise maps of brain metrics such as cortical thickness were mapped into 2D planar images for each brain surface extracted from each person’s MRI scan. Second, several popular networks pretrained on the ImageNet database, i.e., VGG19, ResNet152 and DenseNet201, were used for transfer learning of brain shape metrics. We combined all shape metrics and generated a metric ensemble classification, and then combined all three networks and generated a network ensemble classification. The results reveal that transfer learning always outperforms direct learning, and we obtained accuracies of 65.6±0.7% and 62.7±0.7% for transfer and direct learning in the network ensemble classification, respectively. Moreover, surface area and cortical thickness, especially in the left hemisphere, consistently achieved the highest classification accuracies, together with subcortical shape metrics. The findings suggest a significant and classifiable influence of obesity on brain shape. Our proposed OMTNet method may offer a powerful transfer learning framework that can be extended to other vertex-wise brain structural and functional imaging measures.

The relationship between APOE genotype and subcortical volume: A UK Biobank study (N=36,920)

Alzheimers & Dementia, Dec 1, 2021

Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times... more Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times greater risk for late‐onset Alzheimer’s disease (AD)1,2,3, depending on genetic ancestry. Although reduced hippocampus and amygdala volumes are seen in ε4 carriers with mild cognitive impairment (MCI) and AD4,5, the relationship between genetic risk and brain structure in healthy older adults is unresolved. Here we mapped normative subcortical volume trajectories in a large sample of healthy adults and tested for the effects of APOE genotype.

Advanced diffusion‐weighted MRI methods demonstrate improved sensitivity to white matter aging: Percentile charts for over 15,000 UK Biobank participants

Alzheimers & Dementia, Dec 1, 2021

Aging and Alzheimer’s disease are both associated with alterations in the brain’s white matter. U... more Aging and Alzheimer’s disease are both associated with alterations in the brain’s white matter. Understanding how the brain’s white matter changes as we age may also improve our understanding of processes involved in Alzheimer’s disease. Here we investigated the ability of both traditional and advanced diffusion‐weighted MRI methods to capture age effects on white matter microstructure in a large‐scale, population‐based sample of middle‐aged and older adults.

Alzheimers & Dementia, Dec 1, 2020

Background: Common variants in the APOE gene are associated with cognitive decline, brain atrophy... more Background: Common variants in the APOE gene are associated with cognitive decline, brain atrophy and risk for developing Alzheimer's disease (AD). APOE polymorphism effects may also vary with age, sex, body mass index (BMI), and other risk factors. Here we create percentile charts-or 'nomograms'-plotting the trajectory

White matter microstructure shows sex differences in late childhood: Evidence from 6797 children

Human Brain Mapping, Sep 29, 2022

Sex differences in white matter microstructure have been robustly demonstrated in the adult brain... more Sex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion‐weighted magnetic resonance imaging approaches. However, sex differences in white matter microstructure prior to adulthood remain poorly understood; previous developmental work focused on conventional microstructure metrics and yielded mixed results. Here, we rigorously characterized sex differences in white matter microstructure among over 6000 children from the Adolescent Brain Cognitive Development study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model—diffusion tensor imaging (DTI)—and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. Sex differences in FA were regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.

Alzheimers & Dementia, Dec 1, 2020

Background: Much remains to be understood about subcortical brain alterations across the lifespan... more Background: Much remains to be understood about subcortical brain alterations across the lifespan and how such changes are related to sex and genetic risk for dementia. Here we analyze the effect of sex, age and APOE genotype on subcortical volume and high-resolution morphometry in a large population-based sample. We hypothe

Advanced diffusion-weighted MRI metrics detect sex differences in aging among 15,000 adults in the UK Biobank

The brain’s white matter microstructure, as assessed using diffusion-weighted MRI (DWI), changes ... more The brain’s white matter microstructure, as assessed using diffusion-weighted MRI (DWI), changes significantly with age and also exhibits significant sex differences. Here we examined the ability of a traditional diffusivity metric (fractional anisotropy derived from diffusion tensor imaging, DTI-FA) and advanced diffusivity metrics (fractional anisotropy derived from the tensor distribution function, TDF-FA; neurite orientation dispersion and density imaging measures of intracellular volume fraction, NODDI-ICVF; orientation dispersion index, NODDI-ODI; and isotropic volume fraction, NODDI-ISOVF) to detect sex differences in white matter aging. We also created normative aging reference curves based on sex. Diffusion tensor imaging (DTI) applies a single-tensor diffusion model to single-shell DWI data, while the tensor distribution function (TDF) fits a continuous distribution of tensors to single-shell DWI data. Neurite orientation dispersion and density imaging (NODDI) fits a multi-compartment model to multi-shell DWI data to distinguish intra- and extracellular contributions to diffusion. We analyzed these traditional and advanced diffusion measures in a large population sample available through the UK Biobank (15,394 participants; age-range: 45-80 years) by using linear regression and fractional polynomials. Advanced diffusivity metrics (NODDI-ODI, NODDI-ISOVF, TDF-FA) detected significant sex differences in aging, whereas a traditional metric (DTI-FA) did not. These findings suggest that future studies examining sex differences in white matter aging may benefit from including advanced diffusion measures.

Brain Imaging and Behavior, Sep 18, 2021

A comprehensive characterization of the brain's white matter is critical for improving our unders... more A comprehensive characterization of the brain's white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.

Sex‐dependent age trajectories of subcortical brain volume: A UK Biobank study (N=39,544)

Alzheimers & Dementia, Dec 1, 2021

BackgroundUnderstanding the normative variation in brain structure across life may provide insigh... more BackgroundUnderstanding the normative variation in brain structure across life may provide insights into healthy aging as well as neurological disorders such as Alzheimer’s disease (AD). Women are at greater risk of developing AD, but men tend to show faster rates of subcortical atrophy across adulthood. Sex‐dependent differences in male and female brain aging trajectories may change over the adult lifespan, and could play a role in differential risk for neurological illness. The current study maps normative trajectories (nomograms) of subcortical volume across adulthood and quantifies the interaction between age and sex in a large, healthy sample.MethodT1‐weighted brain MRI from a sample of UK Biobank participants free from psychiatric/neurological illness (; N=39,544; 44.6‐82.8 years) were segmented using FreeSurfer 7.1 to derive average left and right thalamus, putamen, pallidum, hippocampus, amygdala, caudate, nucleus accumbens and ventricle volumes. Normative quantile regression models (nomograms) were created to visualize aging trajectories for each volume. Linear mixed models were fit in binned age groups to assess age‐by‐sex interactions across middle to late adulthood.ResultNomograms showed volumetric loss across adulthood, except for ventricular volume which was larger with increasing age (). Compared to females, males showed a steeper slope of volume change with increasing age in all regions across the full age range (Cohen’s d: ‐0.14 ‐ 0.12) (). Binned‐age analysis showed males to have steeper volume loss trajectories in middle adulthood, with fewer age‐by‐sex interactions detected later in life for most structures.ConclusionIn a large sample of healthy adults, we found a structure‐specific interaction between age and sex, with males tending to show steeper age‐related volume loss trajectories compared to females until later decades of life, where trends appeared similar for men and women. This study provides normative subcortical aging trends and identifies potential sex‐dependent variations across life that may be used to understand healthy brain aging and risk for disorders such as AD.

Subcortical brain trajectories in later life between sexes and APOE genotypes: A UK Biobank study of individuals of self‐identified Indian ancestry

Alzheimers & Dementia, Dec 1, 2021

In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnic... more In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnicities. Most dementia studies mainly examine individuals of European ancestry and/or higher socioeconomic status, making it unclear if effects generalize to other populations. Here we map age trends in subcortical brain morphometry in later life and investigate the modulating effects of sex and APOE genotype in people of self‐identified (SI) Indian ancestry.

Modeling of structural brain variation over the lifespan is important to better understand factor... more Modeling of structural brain variation over the lifespan is important to better understand factors contributing to healthy aging and risk for neurological conditions such as Alzheimer's disease. Even so, we lack normative data on brain morphometry across the adult lifespan in large, well-powered samples. Here, in a large population-based sample of 26,440 adults from the UK Biobank (age: 44-81 yrs.), we created normative percentile charts for MRI-derived subcortical volumes. Next, we investigated associations between these morphometric measures and the strongest known genetic risk factor for late-onset Alzheimer's disease (APOE genotype) and mapped the spatial distribution of age-by-sex interactions using computational surface mesh modeling and shape analysis. Vertex-wise shape mapping supplements traditional gross volumetric approaches to reveal finer-grained variations across functionally important brain subcompartments. Normative curves revealed volumetric loss with age, as expected, for all subcortical brain structures except for the lateral ventricles, which expanded with age. Surprisingly, no volumetric associations with APOE genotype were detected, despite the very large sample size. Age-related trajectories for volumes differed in women versus men, and surface-based statistical maps revealed the spatial distribution of the age-by-sex interaction. Subcortical volumes declined faster in men than women over the full age range, but after age 60, fewer structures showed sex-dependent trajectories, indicating similar volumetric changes in older men and women. Large-scale statistical modeling of age effects on brain structures may drive new insights into individual differences in brain aging and help to identify factors that promote healthy brain aging and risk for disease.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

Alzheimers & Dementia, Dec 1, 2021

The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increa... more The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).

JAMA Psychiatry, Apr 1, 2014

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), but its pathogenesis rem... more IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), but its pathogenesis remains poorly understood. A focus on measuring multisystem quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that affect BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomical phenotypes that appear heritable and associated with severe BP (bipolar I disorder [BP-I]) and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN, SETTING, AND PARTICIPANTS Multigenerational pedigree study in 2 closely related, genetically isolated populations: the Central Valley of Costa Rica and Antioquia, Colombia. A total of 738 individuals, all from Central Valley of Costa Rica and Antioquia pedigrees, participated; among them, 181 have BP-I. MAIN OUTCOMES AND MEASURES Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging, and diffusion tensor imaging phenotypes. RESULTS Of 169 phenotypes investigated, 119 (70%) were significantly heritable and 51 (30%) were associated with BP-I. About one-quarter of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions and volume of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND RELEVANCE To our knowledge, this is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I association within families that is consistent with expectations from case-control studies. Together, these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder.

Alzheimer's & Dementia

BackgroundMuch remains to be understood about subcortical brain alterations across the lifespan a... more BackgroundMuch remains to be understood about subcortical brain alterations across the lifespan and how such changes are related to sex and genetic risk for dementia. Here we analyze the effect of sex, age and APOE genotype on subcortical volume and high‐resolution morphometry in a large population‐based sample. We hypothesized that shape analysis would reveal complex age and sex effects not revealed by gross volumetric analysis and that each copy of the APOE 4 alele would be associated with smaller hippocampal volume.MethodT1‐weighted brain MRI data (N=9,872) from the UK Biobank were processed using FreeSurfer v5.3 to derive bilateral hippocampus, thalamus, putamen, pallidum, amygdala, caudate, nucleus accumbens, lateral ventricle and intracranial volumes (ICV). The ENIGMA Shape Analysis Pipeline was used to compute local thickness and surface area (SA) metrics for up to 2,502 vertices along each structure’s surface (Figure 1). Linear regression was used to model age (44‐79 yrs), s...

Advanced diffusion‐weighted MRI sensitively detects age and sex effects in 34,423 adults

Alzheimers & Dementia, Dec 1, 2022

Subcortical brain structure and APOE genotype: An analysis of 43,000 participants from the UK Biobank

Alzheimer's & Dementia

Subcortical brain trajectories in later life between sexes and APOE genotypes: A UK Biobank study of individuals of self‐identified Indian ancestry

Alzheimer's & Dementia, 2021

In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnic... more In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnicities. Most dementia studies mainly examine individuals of European ancestry and/or higher socioeconomic status, making it unclear if effects generalize to other populations. Here we map age trends in subcortical brain morphometry in later life and investigate the modulating effects of sex and APOE genotype in people of self‐identified (SI) Indian ancestry.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

Alzheimer's & Dementia, 2021

The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increa... more The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).

The relationship between APOE genotype and subcortical volume: A UK Biobank study (N=36,920)

Alzheimer's & Dementia, 2021

Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times... more Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times greater risk for late‐onset Alzheimer’s disease (AD)1,2,3, depending on genetic ancestry. Although reduced hippocampus and amygdala volumes are seen in ε4 carriers with mild cognitive impairment (MCI) and AD4,5, the relationship between genetic risk and brain structure in healthy older adults is unresolved. Here we mapped normative subcortical volume trajectories in a large sample of healthy adults and tested for the effects of APOE genotype.

Effect of APOE4 and APOE2 genotype on white matter microstructure

Alzheimer's & Dementia, 2021

The apolipoprotein E4 (APOE4) genotype is a major risk factor for late‐onset Alzheimer’s disease ... more The apolipoprotein E4 (APOE4) genotype is a major risk factor for late‐onset Alzheimer’s disease (AD). APOE2, on the other hand, has a protective effect. While there is evidence supporting an association between APOE genotype and white matter (WM) microstructure, findings have been inconsistent. Studies assessing AD risk in WM microstructure have largely used diffusion tensor imaging (DTI), but more recent diffusion MRI models may offer additional sensitivity to microstructural properties. Here, we characterized the effects of APOE4 and APOE2 genotypes on WM microstructure in a large, population‐based sample of adults from the UK Biobank.

Deep transfer learning of brain shape morphometry predicts Body Mass Index (BMI) in the UK Biobank

16th International Symposium on Medical Information Processing and Analysis

Prior studies show that obesity is associated with accelerated brain aging and specific patterns ... more Prior studies show that obesity is associated with accelerated brain aging and specific patterns of brain atrophy. Finerscale mapping of the effects of obesity on the brain would help to understand how it promotes or interacts with disease effects, but so far, the influence of the obesity on finer-scale maps of anatomy remains unclear. In this study, we propose a deep transfer learning network based on Optimal Mass Transport (OMTNet) to classify individuals with normal versus overweight/obese body mass index (BMI) using vertex-wise brain shape metrics extracted from structural MRI scans from the UK Biobank study. First, an area-preserving mapping was used to project 3D brain surface meshes onto 2D planar meshes. Vertex-wise maps of brain metrics such as cortical thickness were mapped into 2D planar images for each brain surface extracted from each person’s MRI scan. Second, several popular networks pretrained on the ImageNet database, i.e., VGG19, ResNet152 and DenseNet201, were used for transfer learning of brain shape metrics. We combined all shape metrics and generated a metric ensemble classification, and then combined all three networks and generated a network ensemble classification. The results reveal that transfer learning always outperforms direct learning, and we obtained accuracies of 65.6±0.7% and 62.7±0.7% for transfer and direct learning in the network ensemble classification, respectively. Moreover, surface area and cortical thickness, especially in the left hemisphere, consistently achieved the highest classification accuracies, together with subcortical shape metrics. The findings suggest a significant and classifiable influence of obesity on brain shape. Our proposed OMTNet method may offer a powerful transfer learning framework that can be extended to other vertex-wise brain structural and functional imaging measures.

The relationship between APOE genotype and subcortical volume: A UK Biobank study (N=36,920)

Alzheimers & Dementia, Dec 1, 2021

Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times... more Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times greater risk for late‐onset Alzheimer’s disease (AD)1,2,3, depending on genetic ancestry. Although reduced hippocampus and amygdala volumes are seen in ε4 carriers with mild cognitive impairment (MCI) and AD4,5, the relationship between genetic risk and brain structure in healthy older adults is unresolved. Here we mapped normative subcortical volume trajectories in a large sample of healthy adults and tested for the effects of APOE genotype.

Advanced diffusion‐weighted MRI methods demonstrate improved sensitivity to white matter aging: Percentile charts for over 15,000 UK Biobank participants

Alzheimers & Dementia, Dec 1, 2021

Aging and Alzheimer’s disease are both associated with alterations in the brain’s white matter. U... more Aging and Alzheimer’s disease are both associated with alterations in the brain’s white matter. Understanding how the brain’s white matter changes as we age may also improve our understanding of processes involved in Alzheimer’s disease. Here we investigated the ability of both traditional and advanced diffusion‐weighted MRI methods to capture age effects on white matter microstructure in a large‐scale, population‐based sample of middle‐aged and older adults.

Alzheimers & Dementia, Dec 1, 2020

Background: Common variants in the APOE gene are associated with cognitive decline, brain atrophy... more Background: Common variants in the APOE gene are associated with cognitive decline, brain atrophy and risk for developing Alzheimer's disease (AD). APOE polymorphism effects may also vary with age, sex, body mass index (BMI), and other risk factors. Here we create percentile charts-or 'nomograms'-plotting the trajectory

White matter microstructure shows sex differences in late childhood: Evidence from 6797 children

Human Brain Mapping, Sep 29, 2022

Sex differences in white matter microstructure have been robustly demonstrated in the adult brain... more Sex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion‐weighted magnetic resonance imaging approaches. However, sex differences in white matter microstructure prior to adulthood remain poorly understood; previous developmental work focused on conventional microstructure metrics and yielded mixed results. Here, we rigorously characterized sex differences in white matter microstructure among over 6000 children from the Adolescent Brain Cognitive Development study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model—diffusion tensor imaging (DTI)—and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. Sex differences in FA were regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.

Alzheimers & Dementia, Dec 1, 2020

Background: Much remains to be understood about subcortical brain alterations across the lifespan... more Background: Much remains to be understood about subcortical brain alterations across the lifespan and how such changes are related to sex and genetic risk for dementia. Here we analyze the effect of sex, age and APOE genotype on subcortical volume and high-resolution morphometry in a large population-based sample. We hypothe

Advanced diffusion-weighted MRI metrics detect sex differences in aging among 15,000 adults in the UK Biobank

The brain’s white matter microstructure, as assessed using diffusion-weighted MRI (DWI), changes ... more The brain’s white matter microstructure, as assessed using diffusion-weighted MRI (DWI), changes significantly with age and also exhibits significant sex differences. Here we examined the ability of a traditional diffusivity metric (fractional anisotropy derived from diffusion tensor imaging, DTI-FA) and advanced diffusivity metrics (fractional anisotropy derived from the tensor distribution function, TDF-FA; neurite orientation dispersion and density imaging measures of intracellular volume fraction, NODDI-ICVF; orientation dispersion index, NODDI-ODI; and isotropic volume fraction, NODDI-ISOVF) to detect sex differences in white matter aging. We also created normative aging reference curves based on sex. Diffusion tensor imaging (DTI) applies a single-tensor diffusion model to single-shell DWI data, while the tensor distribution function (TDF) fits a continuous distribution of tensors to single-shell DWI data. Neurite orientation dispersion and density imaging (NODDI) fits a multi-compartment model to multi-shell DWI data to distinguish intra- and extracellular contributions to diffusion. We analyzed these traditional and advanced diffusion measures in a large population sample available through the UK Biobank (15,394 participants; age-range: 45-80 years) by using linear regression and fractional polynomials. Advanced diffusivity metrics (NODDI-ODI, NODDI-ISOVF, TDF-FA) detected significant sex differences in aging, whereas a traditional metric (DTI-FA) did not. These findings suggest that future studies examining sex differences in white matter aging may benefit from including advanced diffusion measures.

Brain Imaging and Behavior, Sep 18, 2021

A comprehensive characterization of the brain's white matter is critical for improving our unders... more A comprehensive characterization of the brain's white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.

Sex‐dependent age trajectories of subcortical brain volume: A UK Biobank study (N=39,544)

Alzheimers & Dementia, Dec 1, 2021

BackgroundUnderstanding the normative variation in brain structure across life may provide insigh... more BackgroundUnderstanding the normative variation in brain structure across life may provide insights into healthy aging as well as neurological disorders such as Alzheimer’s disease (AD). Women are at greater risk of developing AD, but men tend to show faster rates of subcortical atrophy across adulthood. Sex‐dependent differences in male and female brain aging trajectories may change over the adult lifespan, and could play a role in differential risk for neurological illness. The current study maps normative trajectories (nomograms) of subcortical volume across adulthood and quantifies the interaction between age and sex in a large, healthy sample.MethodT1‐weighted brain MRI from a sample of UK Biobank participants free from psychiatric/neurological illness (; N=39,544; 44.6‐82.8 years) were segmented using FreeSurfer 7.1 to derive average left and right thalamus, putamen, pallidum, hippocampus, amygdala, caudate, nucleus accumbens and ventricle volumes. Normative quantile regression models (nomograms) were created to visualize aging trajectories for each volume. Linear mixed models were fit in binned age groups to assess age‐by‐sex interactions across middle to late adulthood.ResultNomograms showed volumetric loss across adulthood, except for ventricular volume which was larger with increasing age (). Compared to females, males showed a steeper slope of volume change with increasing age in all regions across the full age range (Cohen’s d: ‐0.14 ‐ 0.12) (). Binned‐age analysis showed males to have steeper volume loss trajectories in middle adulthood, with fewer age‐by‐sex interactions detected later in life for most structures.ConclusionIn a large sample of healthy adults, we found a structure‐specific interaction between age and sex, with males tending to show steeper age‐related volume loss trajectories compared to females until later decades of life, where trends appeared similar for men and women. This study provides normative subcortical aging trends and identifies potential sex‐dependent variations across life that may be used to understand healthy brain aging and risk for disorders such as AD.

Subcortical brain trajectories in later life between sexes and APOE genotypes: A UK Biobank study of individuals of self‐identified Indian ancestry

Alzheimers & Dementia, Dec 1, 2021

In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnic... more In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnicities. Most dementia studies mainly examine individuals of European ancestry and/or higher socioeconomic status, making it unclear if effects generalize to other populations. Here we map age trends in subcortical brain morphometry in later life and investigate the modulating effects of sex and APOE genotype in people of self‐identified (SI) Indian ancestry.

Modeling of structural brain variation over the lifespan is important to better understand factor... more Modeling of structural brain variation over the lifespan is important to better understand factors contributing to healthy aging and risk for neurological conditions such as Alzheimer's disease. Even so, we lack normative data on brain morphometry across the adult lifespan in large, well-powered samples. Here, in a large population-based sample of 26,440 adults from the UK Biobank (age: 44-81 yrs.), we created normative percentile charts for MRI-derived subcortical volumes. Next, we investigated associations between these morphometric measures and the strongest known genetic risk factor for late-onset Alzheimer's disease (APOE genotype) and mapped the spatial distribution of age-by-sex interactions using computational surface mesh modeling and shape analysis. Vertex-wise shape mapping supplements traditional gross volumetric approaches to reveal finer-grained variations across functionally important brain subcompartments. Normative curves revealed volumetric loss with age, as expected, for all subcortical brain structures except for the lateral ventricles, which expanded with age. Surprisingly, no volumetric associations with APOE genotype were detected, despite the very large sample size. Age-related trajectories for volumes differed in women versus men, and surface-based statistical maps revealed the spatial distribution of the age-by-sex interaction. Subcortical volumes declined faster in men than women over the full age range, but after age 60, fewer structures showed sex-dependent trajectories, indicating similar volumetric changes in older men and women. Large-scale statistical modeling of age effects on brain structures may drive new insights into individual differences in brain aging and help to identify factors that promote healthy brain aging and risk for disease.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

Alzheimers & Dementia, Dec 1, 2021

The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increa... more The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).

JAMA Psychiatry, Apr 1, 2014

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), but its pathogenesis rem... more IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), but its pathogenesis remains poorly understood. A focus on measuring multisystem quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that affect BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomical phenotypes that appear heritable and associated with severe BP (bipolar I disorder [BP-I]) and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN, SETTING, AND PARTICIPANTS Multigenerational pedigree study in 2 closely related, genetically isolated populations: the Central Valley of Costa Rica and Antioquia, Colombia. A total of 738 individuals, all from Central Valley of Costa Rica and Antioquia pedigrees, participated; among them, 181 have BP-I. MAIN OUTCOMES AND MEASURES Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging, and diffusion tensor imaging phenotypes. RESULTS Of 169 phenotypes investigated, 119 (70%) were significantly heritable and 51 (30%) were associated with BP-I. About one-quarter of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions and volume of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND RELEVANCE To our knowledge, this is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I association within families that is consistent with expectations from case-control studies. Together, these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder.

Alzheimer's & Dementia

BackgroundMuch remains to be understood about subcortical brain alterations across the lifespan a... more BackgroundMuch remains to be understood about subcortical brain alterations across the lifespan and how such changes are related to sex and genetic risk for dementia. Here we analyze the effect of sex, age and APOE genotype on subcortical volume and high‐resolution morphometry in a large population‐based sample. We hypothesized that shape analysis would reveal complex age and sex effects not revealed by gross volumetric analysis and that each copy of the APOE 4 alele would be associated with smaller hippocampal volume.MethodT1‐weighted brain MRI data (N=9,872) from the UK Biobank were processed using FreeSurfer v5.3 to derive bilateral hippocampus, thalamus, putamen, pallidum, amygdala, caudate, nucleus accumbens, lateral ventricle and intracranial volumes (ICV). The ENIGMA Shape Analysis Pipeline was used to compute local thickness and surface area (SA) metrics for up to 2,502 vertices along each structure’s surface (Figure 1). Linear regression was used to model age (44‐79 yrs), s...

Advanced diffusion‐weighted MRI sensitively detects age and sex effects in 34,423 adults

Alzheimers & Dementia, Dec 1, 2022

Subcortical brain structure and APOE genotype: An analysis of 43,000 participants from the UK Biobank

Alzheimer's & Dementia

Subcortical brain trajectories in later life between sexes and APOE genotypes: A UK Biobank study of individuals of self‐identified Indian ancestry

Alzheimer's & Dementia, 2021

In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnic... more In the UK, individuals with Indian ancestry show lower rates of dementia compared to other ethnicities. Most dementia studies mainly examine individuals of European ancestry and/or higher socioeconomic status, making it unclear if effects generalize to other populations. Here we map age trends in subcortical brain morphometry in later life and investigate the modulating effects of sex and APOE genotype in people of self‐identified (SI) Indian ancestry.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

Alzheimer's & Dementia, 2021

The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increa... more The incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).

The relationship between APOE genotype and subcortical volume: A UK Biobank study (N=36,920)

Alzheimer's & Dementia, 2021

Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times... more Two copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times greater risk for late‐onset Alzheimer’s disease (AD)1,2,3, depending on genetic ancestry. Although reduced hippocampus and amygdala volumes are seen in ε4 carriers with mild cognitive impairment (MCI) and AD4,5, the relationship between genetic risk and brain structure in healthy older adults is unresolved. Here we mapped normative subcortical volume trajectories in a large sample of healthy adults and tested for the effects of APOE genotype.

Effect of APOE4 and APOE2 genotype on white matter microstructure

Alzheimer's & Dementia, 2021

The apolipoprotein E4 (APOE4) genotype is a major risk factor for late‐onset Alzheimer’s disease ... more The apolipoprotein E4 (APOE4) genotype is a major risk factor for late‐onset Alzheimer’s disease (AD). APOE2, on the other hand, has a protective effect. While there is evidence supporting an association between APOE genotype and white matter (WM) microstructure, findings have been inconsistent. Studies assessing AD risk in WM microstructure have largely used diffusion tensor imaging (DTI), but more recent diffusion MRI models may offer additional sensitivity to microstructural properties. Here, we characterized the effects of APOE4 and APOE2 genotypes on WM microstructure in a large, population‐based sample of adults from the UK Biobank.