Subclinical variations on ECG and their associations with structural brain aging networks.

Impaired cardiac function is associated with cognitive impairment and brain imaging features of aging. Cardiac arrhythmias, including atrial fibrillation, are implicated in clinical and subclinical brain injuries. Even in the absence of a clinical diagnosis, subclinical or prodromal substrates of arrhythmias, including an abnormally long or short P-wave duration (PWD), a measure associated with atrial abnormalities, have been associated with stroke and cognitive decline. However, the extent to which PWD has subclinical influences on overall aging patterns of the brain is not clearly understood. Here, using neuroimaging and ECG data from the UK Biobank, we use a novel regional "brain age" method to identify the brain aging networks associated with abnormal PWD. We find that PWD is inversely associated with accelerated brain aging in the sensorimotor, frontoparietal, ventral attention, and dorsal attention networks, even in the absence of overt cardiac diseases. These findings suggest that detrimental aging outcomes may result from subclinically abnormal PWD.

Different effects of cardiometabolic syndrome on brain age in relation to gender and ethnicity.

BACKGROUND: A growing body of evidence shows differences in the prevalence of cardiometabolic syndrome (CMS) and dementia based on gender and ethnicity. However, there is a paucity of information about ethnic- and gender-specific CMS effects on brain age. We investigated the different effects of CMS on brain age by gender in Korean and British cognitively unimpaired (CU) populations. We also determined whether the gender-specific difference in the effects of CMS on brain age changes depending on ethnicity. METHODS: These analyses used de-identified, cross-sectional data on CU populations from Korea and United Kingdom (UK) that underwent brain MRI. After propensity score matching to balance the age and gender between the Korean and UK populations, 5759 Korean individuals (3042 males and 2717 females) and 9903 individuals from the UK (4736 males and 5167 females) were included in this study. Brain age index (BAI), calculated by the difference between the predicted brain age by the algorithm and the chronological age, was considered as main outcome and presence of CMS, including type 2 diabetes mellitus (T2DM), hypertension, obesity, and underweight was considered as a predictor. Gender (males and females) and ethnicity (Korean and UK) were considered as effect modifiers. RESULTS: The presence of T2DM and hypertension was associated with a higher BAI regardless of gender and ethnicity (p < 0.001), except for hypertension in Korean males (p = 0.309). Among Koreans, there were interaction effects of gender and the presence of T2DM (p for T2DM*gender = 0.035) and hypertension (p for hypertension*gender = 0.046) on BAI in Koreans, suggesting that T2DM and hypertension are each associated with a higher BAI in females than in males. In contrast, among individuals from the UK, there were no differences in the effects of T2DM (p for T2DM*gender = 0.098) and hypertension (p for hypertension*gender = 0.203) on BAI between males and females. CONCLUSIONS: Our results highlight gender and ethnic differences as important factors in mediating the effects of CMS on brain age. Furthermore, these results suggest that ethnic- and gender-specific prevention strategies may be needed to protect against accelerated brain aging.

Brain structure and allelic associations in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic. AIMS: This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations. MATERIALS AND METHODS: The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues. RESULTS: We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models. DISCUSSION: In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC. CONCLUSION: This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

Mapping Complex Brain Torque Components and Their Genetic Architecture and Phenomic Associations in 24,112 Individuals.

BACKGROUND: The functional significance and mechanisms determining the development and individual variability of structural brain asymmetry remain unclear. Here, we systematically analyzed all relevant components of the most prominent structural asymmetry, brain torque (BT), and their relationships with potential genetic and nongenetic modifiers in a sample comprising 24,112 individuals from six cohorts. METHODS: BT features, including petalia, bending, dorsoventral shift, brain tissue distribution asymmetries, and cortical surface positional asymmetries, were directly modeled using a set of automatic three-dimensional brain shape analysis approaches. Age-, sex-, and handedness-related effects on BT were assessed. The genetic architecture and phenomic associations of BT were investigated using genome- and phenome-wide association scans. RESULTS: Our results confirmed the population-level predominance of the typical counterclockwise torque and suggested a first attenuating, then enlarging dynamic across the life span (3-81 years) primarily for frontal, occipital, and perisylvian BT features. Sex/handedness, BT, and cognitive function of verbal-numerical reasoning were found to be interrelated statistically. We observed differential heritability of up to 56% for BT, especially in temporal language areas. Individual variations of BT were also associated with various phenotypic variables of neuroanatomy, cognition, lifestyle, sociodemographics, anthropometry, physical health, and adult and child mental health. Our genomic analyses identified a number of genetic associations at lenient significance levels, which need to be further validated using larger samples in the future. CONCLUSIONS: This study provides a comprehensive description of BT and insights into biological and other factors that may contribute to the development and individual variations of BT.

Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies.

Large-scale, case-control genome-wide association studies (GWASs) have revealed genetic variations associated with diverse neurological and psychiatric disorders. Recent advances in neuroimaging and genomic databases of large healthy and diseased cohorts have empowered studies to characterize effects of the discovered genetic factors on brain structure and function, implicating neural pathways and genetic mechanisms in the underlying biology. However, the unprecedented scale and complexity of the imaging and genomic data requires new advanced biomedical data science tools to manage, process and analyze the data. In this work, we introduce Neuroimaging PheWAS (phenome-wide association study): a web-based system for searching over a wide variety of brain-wide imaging phenotypes to discover true system-level gene-brain relationships using a unified genotype-to-phenotype strategy. This design features a user-friendly graphical user interface (GUI) for anonymous data uploading, study definition and management, and interactive result visualizations as well as a cloud-based computational infrastructure and multiple state-of-art methods for statistical association analysis and multiple comparison correction. We demonstrated the potential of Neuroimaging PheWAS with a case study analyzing the influences of the apolipoprotein E (APOE) gene on various brain morphological properties across the brain in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Benchmark tests were performed to evaluate the system's performance using data from UK Biobank. The Neuroimaging PheWAS system is freely available. It simplifies the execution of PheWAS on neuroimaging data and provides an opportunity for imaging genetics studies to elucidate routes at play for specific genetic variants on diseases in the context of detailed imaging phenotypic data.

Interaction effect of alcohol consumption and Alzheimer disease polygenic risk score on the brain cortical thickness of cognitively normal subjects.

Alcohol consumption and genetic risk for Alzheimer disease (AD) are among many factors known to be associated with brain structure in cognitively healthy adults. It is unclear, however, whether the effect of alcohol consumption on brain structure varies depending on a person's level of genetic risk for AD. We hypothesized that there is an interaction effect of alcohol consumption and a 33-SNP AD polygenic risk score (PRS) on the cortical thickness of brain regions known to be affected early in the course of AD. Studying 6,213 cognitively healthy subjects from the UK Biobank, we found a significant interaction effect of the 33-SNP AD PRS and alcohol consumption on this AD Cortical Thickness Signature. Stratified, among those who consume 12-24 g/day of alcohol, the 33-SNP AD PRS had a significant, positive association with AD Cortical Thickness Signature, with high-risk subjects having the greatest AD Cortical Thickness Signature. There were no significant associations of the 33-SNP AD PRS with AD Cortical Thickness Signature among the nondrinker or <1, 1-6, 6-12, 24-48, or >48 g/day groups. It is unclear whether this interaction is due to a detrimental or beneficial effect of moderate alcohol consumption in those with the highest genetic risk for AD.

Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults.

Brain structural morphology differs with age. This study examined age-differences in surface-based morphometric measures of cortical thickness, volume, and surface area in a well-defined sample of 8137 generally healthy UK Biobank participants aged 45-79 years. We illustrate that the complexity of age-related brain morphological differences may be related to the laminar organization and regional evolutionary history of the cortex, and age of about 60 is a break point for increasing negative associations between age and brain morphology in Alzheimer's disease (AD)-prone areas. We also report novel relationships of age-related cortical differences with individual factors of sex, cognitive functions of fluid intelligence, reaction time and prospective memory, cigarette smoking, alcohol consumption, sleep disruption, genetic markers of apolipoprotein E, brain-derived neurotrophic factor, catechol-O-methyltransferase, and several genome-wide association study loci for AD and further reveal joint effects of cognitive functions, lifestyle behaviors, and education on age-related cortical differences. These findings provide one of the most extensive characterizations of age associations with major brain morphological measures and improve our understanding of normal structural brain aging and its potential modifiers.

Scaling and systems biology for integrating multiple organs-on-a-chip.

Coupled systems of in vitro microfabricated organs-on-a-chip containing small populations of human cells are being developed to address the formidable pharmacological and physiological gaps between monolayer cell cultures, animal models, and humans that severely limit the speed and efficiency of drug development. These gaps present challenges not only in tissue and microfluidic engineering, but also in systems biology: how does one model, test, and learn about the communication and control of biological systems with individual organs-on-chips that are one-thousandth or one-millionth of the size of adult organs, or even smaller, i.e., organs for a milliHuman (mHu) or microHuman (µHu)? Allometric scaling that describes inter-species variation of organ size and properties provides some guidance, but given the desire to utilize these systems to extend and validate human pharmacokinetic and pharmacodynamic (PK/PD) models in support of drug discovery and development, it is more appropriate to scale each organ functionally to ensure that it makes the suitable physiological contribution to the coupled system. The desire to recapitulate the complex organ-organ interactions that result from factors in the blood and lymph places a severe constraint on the total circulating fluid (~5 mL for a mHu and ~5 µL for a µHu) and hence on the pumps, valves, and analytical instruments required to maintain and study these systems. Scaling arguments also provide guidance on the design of a universal cell-culture medium, typically without red blood cells. This review presents several examples of scaling arguments and discusses steps that should ensure the success of this endeavour.