Frithjof Kruggel

Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease

Background With the exception of APOE ε4 allele, the common genetic risk factors for sporadic Alzheimers Disease (AD) are unknown. Methods and Findings We completed a genome-wide association study on 381 participants in the ADNI (Alzheimers Disease Neuroimaging Initiative) study. Samples were genotyped using the Illumina Human610-Quad BeadChip. 516,645 unique Single Nucleotide Polymorphisms (SNPs) were included in the analysis following quality control measures. The genotype data and raw genetic data are freely available for download (LONI, http://www.loni.ucla.edu/ADNI/Data/). Two analyses were completed: a standard case-control analysis, and a novel approach using hippocampal atrophy measured on MRI as an objectively defined, quantitative phenotype. A General Linear Model was applied to identify SNPs for which there was an interaction between the genotype and diagnosis on the quantitative trait. The case-control analysis identified APOE and a new risk gene, TOMM40 (translocase of outer mitochondrial membrane 40), at a genome-wide significance level of≤10−6 (10−11 for a haplotype). TOMM40 risk alleles were approximately twice as frequent in AD subjects as controls. The quantitative trait analysis identified 21 genes or chromosomal areas with at least one SNP with a p-value≤10−6, which can be considered potential “new” candidate loci to explore in the etiology of sporadic AD. These candidates included EFNA5, CAND1, MAGI2, ARSB, and PRUNE2, genes involved in the regulation of protein degradation, apoptosis, neuronal loss and neurodevelopment. Thus, we identified common genetic variants associated with the increased risk of developing AD in the ADNI cohort, and present publicly available genome-wide data. Supportive evidence based on case-control studies and biological plausibility by gene annotation is provided. Currently no available sample with both imaging and genetic data is available for replication. Conclusions Using hippocampal atrophy as a quantitative phenotype in a genome-wide scan, we have identified candidate risk genes for sporadic Alzheimers disease that merit further investigation.

MRI-based volumetry of head compartments: normative values of healthy adults.

The size of head compartments (head and brain volume, intracranial volume, gray and white matter volume, cerebrospinal fluid volume) and their ratios were determined on the basis of magnetic resonance images of the head acquired in a reference population of 502 healthy subjects. Age-matched subgroups were selected to reveal gender-related differences and changes with age. Normative data are provided in the form of simple equations that allow transforming measured compartment volumes into z scores, offering the possibility to relate individual data to a larger population.

Impact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort

Morphometry of brain structures based on magnetic resonance imaging (MRI) data has become an important tool in neurobiology. Recent multicenter studies in neurodegenerative diseases raised the issue of the precision of volumetric measures, and their dependence on the scanner properties and imaging protocol. A large dataset consisting of 1073 MRI examinations in 843 subjects, acquired on 90 scanners at 58 sites, is analyzed here. A comprehensive set of image quality and content measures is used to describe the influence of the scanner hardware and imaging protocol on the variability of morphometric measures. Scanners equipped with array coils show a remarkable advantage over conventional coils in terms of image quality measures. The signal- and contrast-to-noise ratio in similar systems is equal or slightly better at 1.5 T than 3.0 T, while the white/grey matter tissue contrast is generally better on high-field systems. Repeated MRI investigations on the same scanner were available in 41 subjects, on different scanners in 172 subjects. The retest reliability of repeated volumetric measures under the same conditions was found as sufficient to track changes in longitudinal examinations in individual subjects. Using different acquisition conditions in the same subject, however, the variance of volumetric measures was up to 10 times greater. Two likely factors explaining this finding are scanner-dependent geometrical inaccuracies and differences in the white/grey matter tissue contrast.

Behavioral and neuroanatomical investigation of Highly Superior Autobiographical Memory (HSAM)

A single case study recently documented one womans ability to recall accurately vast amounts of autobiographical information, spanning most of her lifetime, without the use of practiced mnemonics (Parker, Cahill, & McGaugh, 2006). The current study reports findings based on eleven participants expressing this same memory ability, now referred to as Highly Superior Autobiographical Memory (HSAM). Participants were identified and subsequently characterized based on screening for memory of public events. They were then tested for personal autobiographical memories as well as for memory assessed by laboratory memory tests. Additionally, whole-brain structural MRI scans were obtained. Results indicated that HSAM participants performed significantly better at recalling public as well as personal autobiographical events as well as the days and dates on which these events occurred. However, their performance was comparable to age- and sex-matched controls on most standard laboratory memory tests. Neuroanatomical results identified nine structures as being morphologically different from those of control participants. The study of HSAM may provide new insights into the neurobiology of autobiographical memory.

Texture-based segmentation of diffuse lesions of the brain's white matter.

Diffuse lesions of the white matter of the human brain are common pathological findings in magnetic resonance images of elderly subjects. These lesions are typically caused by small vessel diseases (e.g., due to hypertension, diabetes), and related to cognitive decline. Because these lesions are inhomogeneous, unsharp, and faint, but show an intensity pattern that is different from the adjacent healthy tissue, a segmentation based on texture properties is proposed here. This method was successfully applied to a set of 116 image data sets of elderly subjects. Quantitative measures for the lesion load are derived that compare well with results from experts that visually rated lesions on a semiquantitative scale. Texture-based segmentation can be considered as a general method for lesion segmentation, and an outline for adapting this method to similar problems is presented.

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

This article presents a simple method for estimating the effective diffusion coefficients parallel and perpendicular to the axons unconfounded by the intravoxel fiber orientation distribution. We also call these parameters the per‐axon or microscopic diffusion coefficients.

Automatic segmentation of human brain sulci

The neocortical surface has a rich and complex structure comprised of folds (gyri) and fissures (sulci). Sulci are important macroscopic landmarks for orientation on the cortex. A precise segmentation and labeling of sulci is helpful in human brain mapping studies relating brain anatomy and function. Due to their structural complexity and inter-subject variability, this is considered as a non-trivial task. An automatic algorithm is proposed to accurately segment neocortical sulci: vertices of a white/gray matter interface mesh are classified under a Bayesian framework as belonging to gyral and sulcal compartments using information about their geodesic depth and local curvature. Then, vertices are collected into sulcal regions by a watershed-like growing method. Experimental results demonstrate that the method is accurate and robust.

Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain.

Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function.

In vivo parahippocampal white matter pathology as a biomarker of disease progression to Alzheimer's disease

Noninvasive diagnostic tests for Alzheimers disease (AD) are limited. Postmortem diagnosis is based on density and distribution of neurofibrillary tangles (NFTs) and amyloid‐rich neuritic plaques. In preclinical stages of AD, the cells of origin for the perforant pathway within the entorhinal cortex are among the first to display NFTs, indicating its compromise in early stages of AD. We used diffusion tensor imaging (DTI) to assess the integrity of the parahippocampal white matter in mild cognitive impairment (MCI) and AD, as a first step in developing a noninvasive tool for early diagnosis. Subjects with AD (N = 9), MCI (N = 8), or no cognitive impairment (NCI; N = 20) underwent DTI‐MRI. Fractional anisotropy (FA) and mean (MD) and radial (RD) diffusivity measured from the parahippocampal white matter in AD and NCI subjects differed greatly. Discriminant analysis in the MCI cases assigned statistical membership of 38% of MCI subjects to the AD group. Preliminary data 1 year later showed that all MCI cases assigned to the AD group either met the diagnostic criteria for probable AD or showed significant cognitive decline. Voxelwise analysis in the parahippocampal white matter revealed a progressive change in the DTI patterns in MCI and AD subjects: whereas converted MCI cases showed structural changes restricted to the anterior portions of this region, in AD the pathology was generalized along the entire anterior–posterior axis. The use of DTI for in vivo assessment of the parahippocampal white matter may be useful for identifying individuals with MCI at highest risk for conversion to AD and for assessing disease progression. J. Comp. Neurol. 521:4300–4317, 2013.

Empirical derivation of the reference region for computing diagnostic sensitive 18fluorodeoxyglucose ratios in Alzheimer's disease based on the ADNI sample ☆ ☆☆

Careful selection of the reference region for non-quantitative positron emission tomography (PET) analyses is critically important for Region of Interest (ROI) data analyses. We introduce an empirical method of deriving the most suitable reference region for computing neurodegeneration sensitive (18)fluorodeoxyglucose (FDG) PET ratios based on the dataset collected by the Alzheimers Disease Neuroimaging Initiative (ADNI) study. Candidate reference regions are selected based on a heat map of the difference in coefficients of variation (COVs) of FDG ratios over time for each of the Automatic Anatomical Labeling (AAL) atlas regions normalized by all other AAL regions. Visual inspection of the heat map suggests that the portion of the cerebellum and vermis superior to the horizontal fissure is the most sensitive reference region. Analyses of FDG ratio data show increases in significance on the order of ten-fold when using the superior portion of the cerebellum as compared with the traditionally used full cerebellum. The approach to reference region selection in this paper can be generalized to other radiopharmaceuticals and radioligands as well as to other disorders where brain changes over time are hypothesized and longitudinal data is available. Based on the empirical evidence presented in this study, we demonstrate the usefulness of the COV heat map method and conclude that intensity normalization based on the superior portion of the cerebellum may be most sensitive to measuring change when performing longitudinal analyses of FDG-PET ratios as well as group comparisons in Alzheimers disease. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.