Blood pressure and cerebral white matter share common genetic factors in Mexican Americans

Impact of excessive abdominal obesity on brain microstructural abnormality in schizophrenia

Significant evidence links obesity and schizophrenia (SZ), but the brain associations are still largely unclear. 48 people with SZ were divided into two subgroups: patients with lower waist circumference (SZ-LWC: n = 24) and patients with higher waist circumference (SZ-HWC: n = 24). Healthy controls (HC) were included for comparison (HC: n = 27). Using tract-based spatial statistics, we compared fractional anisotropy (FA) of the whole-brain white matter skeleton between these three groups (SZ-LWC, SZ-HWC, HC). Using Free Surfer, we compared whole-brain cortical thickness and the selected subcortical volumes between the three groups. FA of widespread white matter and the mean cortical thickness in the right temporal lobe and insular cortex were significantly lower in the SZ-HWC group than in the HC group. The FA of regional white matter was significantly lower in the SZ-LWC group than in the HC group. There were no significant differences in mean subcortical volumes between the groups. Additionally, the cognitive performances were worse in the SZ-HWC group, who had more severe triglycerides elevation. This study provides evidence for microstructural abnormalities of white matter, cortical thickness and neurocognitive deficits in SZ patients with excessive abdominal obesity.

Elevated blood pressure accelerates white matter brain aging among late middle-aged women: a Mendelian Randomization study in the UK Biobank

BACKGROUND

Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter brain aging remains unclear.

METHODS

In this study, we focused on N  = 228 473 individuals of European ancestry who had genotype data and clinical BP measurements available (103 929 men and 124 544 women, mean age = 56.49, including 16 901 participants with neuroimaging data available) collected from UK Biobank (UKB). We first established a machine learning model to compute the outcome variable brain age gap (BAG) based on white matter microstructure integrity measured by fractional anisotropy derived from diffusion tensor imaging data. We then performed a two-sample Mendelian randomization analysis to estimate the causal effect of BP on white matter BAG in the whole population and subgroups stratified by sex and age brackets using two nonoverlapping data sets.

RESULTS

The hypertension group is on average 0.31 years (95% CI = 0.13-0.49; P  < 0.0001) older in white matter brain age than the nonhypertension group. Women are on average 0.81 years (95% CI = 0.68-0.95; P  < 0.0001) younger in white matter brain age than men. The Mendelian randomization analyses showed an overall significant positive causal effect of DBP on white matter BAG (0.37 years/10 mmHg, 95% CI 0.034-0.71, P  = 0.0311). In stratified analysis, the causal effect was found most prominent among women aged 50-59 and aged 60-69.

CONCLUSION

High BP can accelerate white matter brain aging among late middle-aged women, providing insights on planning effective control of BP for women in this age group.

Blood pressure-related white matter microstructural disintegrity and associated cognitive function impairment in asymptomatic adults

BACKGROUND AND OBJECTIVES

We aimed to investigate the white matter (WM) microstructural/cytostructural disintegrity patterns related to higher systolic blood pressure (SBP), and whether they mediate SBP effects on cognitive performance in middle-aged adults.

METHODS

Using the UK Biobank study of community-dwelling volunteers aged 40-69 years, we included participants without a history of stroke, dementia, demyelinating disease or traumatic brain injury. We investigated the association of SBP with MRI diffusion metrics: fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (a measure of neurite density), isotropic (free) water volume fraction (ISOVF) and orientation dispersion across WM tracts. Then, we determined whether WM diffusion metrics mediated the effects of SBP on cognitive function.

RESULTS

We analysed 31 363 participants-mean age of 63.8 years (SD: 7.7), and 16 523 (53%) females. Higher SBP was associated with lower FA and neurite density, but higher MD and ISOVF. Among different WM tracts, diffusion metrics of the internal capsule anterior limb, external capsule, superior and posterior corona radiata were most affected by higher SBP. Among seven cognitive metrics, SBP levels were only associated with 'fluid intelligence' (adjusted p<0.001). In mediation analysis, the averaged FA of external capsule, internal capsule anterior limb and superior cerebellar peduncle mediated 13%, 9% and 13% of SBP effects on fluid intelligence, while the averaged MD of external capsule, internal capsule anterior and posterior limbs, and superior corona radiata mediated 5%, 7%, 7% and 6% of SBP effects on fluid intelligence, respectively.

DISCUSSION

Among asymptomatic adults, higher SBP is associated with pervasive WM microstructure disintegrity, partially due to reduced neuronal count, which appears to mediate SBP adverse effects on fluid intelligence. Diffusion metrics of select WM tracts, which are most reflective of SBP-related parenchymal damage and cognitive impairment, may serve as imaging biomarkers to assess treatment response in antihypertensive trials.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

Towards the multileveled and processual conceptualisation of racialised individuals in biomedical research

In this paper, we discuss the processes of racialisation on the example of biomedical research. We argue that applying the concept of racialisation in biomedical research can be much more precise, informative and suitable than currently used categories, such as race and ethnicity. For this purpose, we construct a model of the different processes affecting and co-shaping the racialisation of an individual, and consider these in relation to biomedical research, particularly to studies on hypertension. We finish with a discussion on the potential application of our proposition to institutional guidelines on the use of racial categories in biomedical research.

The additive impact of cardio-metabolic disorders and psychiatric illnesses on accelerated brain aging

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio‐metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning “BrainAge” index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD− (N = 964), SMI−/CMD+ (N = 3,765), SMI−/CMD− (N = 8,083). SMI (F = 40.47, p = 2.06 × 10⁻¹⁰) and CMD (F = 24.69, p = 6.82 × 10⁻⁷) significantly, independently impacted whole‐brain QRI in SMI+. SSD had the largest effect (Cohen’s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI− (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole‐brain QRI was significantly (p < 10⁻¹⁶) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p < 10⁻¹⁶). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio‐metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age‐related cognitive decline.

Blood Pressure Control and Protection of the Aging Brain

Hypertension and dementia are both common disorders whose prevalence increases with age. There are multiple mechanisms by which hypertension affects the brain and alters cognition. These include blood flow dynamics, development of large and small vessel pathology and diverse molecular mechanisms including formation of reactive oxygen species and transcriptional cascades. Blood pressure interacts with Alzheimer disease pathology in numerous and unpredictable ways, affecting both β-amyloid and tau deposition, while also interacting with AD genetic risk factors and other metabolic processes. Treatment of hypertension may prevent cognitive decline and dementia, but methodological issues have limited the ability of randomized clinical trials to show this conclusively. Recent studies have raised hope that hypertension treatment may protect the function and structure of the aging brain from advancing to mild cognitive impairment and dementia.

White matter and hypoxic hypobaria in humans

Occupational exposure to hypobaria (low atmospheric pressure) is a risk factor for reduced white matter integrity, increased white matter hyperintensive burden, and decline in cognitive function. We tested the hypothesis that a discrete hypobaric exposure will have a transient impact on cerebral physiology. Cerebral blood flow, fractional anisotropy of water diffusion in cerebral white matter, white matter hyperintensity volume, and concentrations of neurochemicals were measured at baseline and 24 hr and 72 hr postexposure in N = 64 healthy aircrew undergoing standard US Air Force altitude chamber training and compared to N = 60 controls not exposed to hypobaria. We observed that hypobaric exposure led to a significant rise in white matter cerebral blood flow (CBF) 24 hr postexposure that remained elevated, albeit not significantly, at 72 hr. No significant changes were observed in structural measurements or gray matter CBF. Subjects with higher baseline concentrations of neurochemicals associated with neuroprotection and maintenance of normal white matter physiology (glutathione, N-acetylaspartate, glutamate/glutamine) showed proportionally less white matter CBF changes. Our findings suggest that discrete hypobaric exposure may provide a model to study white matter injury associated with occupational hypobaric exposure.

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r ∼0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web-based calculator (www.solar-eclipse-genetics.org/HCP).

Hypertension and Cerebral Microangiopathy (Cerebral Small Vessel Disease): Genetic and Epigenetic Aspects of Their Relationship

Hypertension (HT) and its cerebral complications are extremely vexing medical and social problems. Despite the obvious association between hypertension and the clinical and neuroimaging features of cerebral microangiopathy (CMA) (also known as cerebral small vessel disease), the causal links between them remain ambiguous. Besides, antihypertensive therapy as the only way to manage these patients does not always prevent brain damage. Knowledge about the key factors and mechanisms involved in HT and CMA development is important for predicting the risk of cerebral complications and developing new approaches to their prevention and treatment. At present, genome-wide association studies and other approaches are used to investigate the common hereditary mechanisms of HT and CMA development, which will explain a large number of CMA cases not associated with hypertension, lack of a correlation between HT severity and the degree of cerebral injury, and failure of antihypertensive therapy to prevent CMA progression. Epigenetic markers likely play a modulating role in the development of these diseases.

Lipid Metabolism, Abdominal Adiposity, and Cerebral Health in the Amish

OBJECTIVE

To assess the association between peripheral lipid/fat profiles and cerebral gray matter (GM) and white matter (WM) in healthy Old Order Amish (OOA).

METHODS

Blood lipids, abdominal adiposity, liver lipid contents, and cerebral microstructure were assessed in OOA (N = 64, 31 males/33 females, ages 18-77). Orthogonal factors were extracted from lipid and imaging adiposity measures. GM assessment used the Human Connectome Project protocol to measure whole-brain average cortical thickness. Diffusion-weighted imaging was used to derive WM fractional anisotropy and kurtosis anisotropy measurements.

RESULTS

Lipid/fat measures were captured by three orthogonal factors explaining 80% of the variance. Factor one loaded on cholesterol and/or low-density lipoprotein cholesterol measurements; factor two loaded on triglyceride/liver measurements; and factor three loaded on abdominal fat measurements. A two-stage regression including age/sex (first stage) and the three factors (second stage) examined the peripheral lipid/fat effects. Factors two and three significantly contributed to WM measures after Bonferroni corrections (P < 0.007). No factor significantly contributed to GM. Blood pressure (BP) inclusion did not meaningfully alter the lipid/fat-WM relationship.

CONCLUSIONS

Peripheral lipid/fat indicators were significantly and negatively associated with cerebral WM rather than with GM, independent of age and BP level. Dissecting the fat/lipid components contributing to different brain imaging parameters may open a new understanding of the body-brain connection through lipid metabolism.

White matter disease in midlife is heritable, related to hypertension, and shares some genetic influence with systolic blood pressure

White matter disease in the brain increases with age and cardiovascular disease, emerging in midlife, and these associations may be influenced by both genetic and environmental factors. We examined the frequency, distribution, and heritability of abnormal white matter and its association with hypertension in 395 middle-aged male twins (61.9 ± 2.6 years) from the Vietnam Era Twin Study of Aging, 67% of whom were hypertensive. A multi-channel segmentation approach estimated abnormal regions within the white matter. Using multivariable regression models, we characterized the frequency distribution of abnormal white matter in midlife and investigated associations with hypertension and Apolipoprotein E-ε4 status and the impact of duration and control of hypertension. Then, using the classical twin design, we estimated abnormal white matter heritability and the extent of shared genetic overlap with blood pressure. Abnormal white matter was predominantly located in periventricular and deep parietal and frontal regions; associated with age (t = 1.9, p = 0.05) and hypertension (t = 2.9, p = 0.004), but not Apolipoprotein ε4 status; and was greater in those with uncontrolled hypertension relative to controlled (t = 3.0, p = 0.003) and normotensive (t = 4.0, p = 0.0001) groups, suggesting that abnormal white matter may reflect currently active cerebrovascular effects. Abnormal white matter was highly heritable (a2 = 0.81) and shared some genetic influences with systolic blood pressure (rA = 0.26), although there was evidence for distinct genetic contributions and unique environmental influences. Future longitudinal research will shed light on factors impacting white matter disease presentation, progression, and potential recovery.

Heterochronicity of white matter development and aging explains regional patient control differences in schizophrenia

BACKGROUND

Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging.

METHODS

Three cohorts of schizophrenia patients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions.

RESULTS

In mega-analysis of whole-brain averaged FA, schizophrenia patients had lower FA (P = 10^-11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org.

CONCLUSION

WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016. © 2016 Wiley Periodicals, Inc.

Shared genetic variance between obesity and white matter integrity in Mexican Americans

Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m²) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h² = 0.58), WC (h² = 0.57), and FA (h² = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors.

Accelerated white matter aging in schizophrenia: role of white matter blood perfusion

Elevated rate of age-related decline in white matter integrity, indexed by fractional anisotropy (FA) from diffusion tensor imaging, was reported in patients with schizophrenia. Its etiology is unknown. We hypothesized that a decline of blood perfusion to the white matter may underlie the accelerated age-related reduction in FA in schizophrenia. Resting white matter perfusion and FA were collected using pseudo-continuous arterial spin labeling and high-angular-resolution diffusion tensor imaging, respectively, in 50 schizophrenia patients and 70 controls (age = 18-63 years). Main outcome measures were the diagnosis-by-age interaction on whole-brain white matter perfusion, and FA. Significant age-related decline in brain white matter perfusion and FA were present in both groups. Age-by-diagnosis interaction was significant for FA (p < 0.001) but not white matter perfusion. Age-by-diagnosis interaction for FA values remained significant even after accounting for age-related decline in perfusion. Therefore, we replicated the finding of an increased rate of age-related white matter FA decline in schizophrenia and observed a significant age-related decline in white matter blood perfusion, although the latter did not contribute to the accelerated age-related decline in FA. The results suggest that factors other than reduced perfusion account for the accelerated age-related decline in white matter integrity in schizophrenia.

Multimodal white matter imaging to investigate reduced fractional anisotropy and its age-related decline in schizophrenia

We hypothesized that reduced fractional anisotropy (FA) of water diffusion and its elevated aging-related decline in schizophrenia patients may be caused by elevated hyperintensive white matter (HWM) lesions, by reduced permeability-diffusivity index (PDI), or both. We tested this hypothesis in 40/30 control/patient participants. FA values for the corpus callosum were calculated from high angular resolution diffusion tensor imaging (DTI). Whole-brain volume of HWM lesions was quantified by 3D-T2w-fluid-attenuated inversion recovery (FLAIR) imaging. PDI for corpus callosum was ascertained using multi b-value diffusion imaging (15 b-shells with 30 directions per shell). Patients had significantly lower corpus callosum FA values, and there was a significant age-by-diagnosis interaction. Patients also had significantly reduced PDI but no difference in HWM volume. PDI and HWM volume were significant predictors of FA and captured the diagnosis-related variance. Separately, PDI robustly explained FA variance in schizophrenia patients, but not in controls. Conversely, HWM volume made equally significant contributions to variability in FA in both groups. The diagnosis-by-age effect of FA was explained by a PDI-by-diagnosis interaction. Post hoc testing showed a similar trend for PDI of gray mater. Our study demonstrated that reduced FA and its accelerated decline with age in schizophrenia were explained by pathophysiology indexed by PDI, rather than HWM volume.

Combining diffusion tensor imaging and magnetic resonance spectroscopy to study reduced frontal white matter integrity in youths with family histories of substance use disorders

Individuals with a family history of substance use disorder (FH+) show impaired frontal white matter as indicated by diffusion tensor imaging (DTI). This impairment may be due to impaired or delayed development of myelin in frontal regions, potentially contributing to this population's increased risk for developing substance use disorders. In this study, we examined high angular resolution DTI and proton magnetic resonance spectroscopy data from the anterior corona radiata were collected in 80 FH+ and 34 FH- youths (12.9 ± 1.0 years old). White matter integrity indices included fractional anisotropy (FA), N-acetylaspartate (NAA), and total choline (tCho). Lower FA suggests decreased myelination. Decreased NAA coupled with higher tCho suggests impaired build-up and maintenance of cerebral myelin and consequently greater breakdown of cellular membranes. We found FH+ youths had lower FA (P < 0.0001) and NAA (P = 0.017) and higher tCho (P = 0.04). FH density (number of parents and grandparents with substance use disorders) was negatively correlated with FA (P < 0.0001) and NAA (P = 0.011) and positively correlated with tCho (P = 0.001). FA was independently predicted by both FH density (P = 0.006) and NAA (P = 0.002), and NAA and tCho were both independent predictors of FH density (P < 0.001). Our finding of lower frontal FA in FH+ youths corresponding to lower NAA and increased tCho is consistent with delayed or impaired development of frontal white matter in FH+ youths. Longitudinal studies are needed to determine how these differences relate to substance use outcomes.

Lower neurocognitive function in U-2 pilots: Relationship to white matter hyperintensities

OBJECTIVE

Determine whether United States Air Force (USAF) U-2 pilots (U2Ps) with occupational exposure to repeated hypobaria had lower neurocognitive performance compared to pilots without repeated hypobaric exposure and whether U2P neurocognitive performance correlated with white matter hyperintensity (WMH) burden.

METHODS

We collected Multidimensional Aptitude Battery-II (MAB-II) and MicroCog: Assessment of Cognitive Functioning (MicroCog) neurocognitive data on USAF U2Ps with a history of repeated occupational exposure to hypobaria and compared these with control data collected from USAF pilots (AFPs) without repeated hypobaric exposure (U2Ps/AFPs MAB-II 87/83; MicroCog 93/80). Additional comparisons were performed between U2Ps with high vs low WMH burden.

RESULTS

U2Ps with repeated hypobaric exposure had significantly lower scores than control pilots on reasoning/calculation (U2Ps/AFPs 99.4/106.5), memory (105.5/110.9), information processing accuracy (102.1/105.8), and general cognitive functioning (103.5/108.5). In addition, U2Ps with high whole-brain WMH count showed significantly lower scores on reasoning/calculation (high/low 96.8/104.1), memory (102.9/110.2), general cognitive functioning (101.5/107.2), and general cognitive proficiency (103.6/108.8) than U2Ps with low WMH burden (high/low WMH mean volume 0.213/0.003 cm(3) and mean count 14.2/0.4).

CONCLUSION

In these otherwise healthy, highly functioning individuals, pilots with occupational exposure to repeated hypobaria demonstrated lower neurocognitive performance, albeit demonstrable on only some tests, than pilots without repeated exposure. Furthermore, within the U2P population, higher WMH burden was associated with lower neurocognitive test performance. Hypobaric exposure may be a risk factor for subtle changes in neurocognition.

Neurodevelopmental and neurodegenerative models of schizophrenia: white matter at the center stage

Schizophrenia is a disorder of cerebral disconnectivity whose lifetime course is modeled as both neurodevelopmental and neurodegenerative. The neurodevelopmental models attribute schizophrenia to alterations in the prenatal-to-early adolescent development. The neurodegenerative models identify progressive neurodegeneration as its core attribute. Historically, the physiology, pharmacology, and treatment targets in schizophrenia were conceptualized in terms of neurons, neurotransmitter levels, and synaptic receptors. Much of the evidence for both models was derived from studies of cortical and subcortical gray matter. We argue that the dynamics of the lifetime trajectory of white matter, and the consistency of connectivity deficits in schizophrenia, support white matter integrity as a promising phenotype to evaluate the competing evidence for and against neurodevelopmental and neurodegenerative heuristics. We develop this perspective by reviewing normal lifetime trajectories of white and gray matter changes. We highlighted the overlap between the age of peak of white matter development and the age of onset of schizophrenia and reviewed findings of white matter abnormalities prior to, at the onset, and at chronic stages of schizophrenia. We emphasized the findings of reduced white matter integrity at the onset and findings of accelerated decline in chronic stages, but the developmental trajectory that precedes the onset is largely unknown. We propose 4 probable lifetime white matter trajectory models that can be used as the basis for separation between the neurodevelopmental and neurodegenerative etiologies. We argue that a combination of the cross-sectional and longitudinal studies of white matter integrity in patients may be used to bridge the neurodevelopment and degeneration heuristics to advance schizophrenia research.

Corpus callosum size is highly heritable in humans, and may reflect distinct genetic influences on ventral and rostral regions

Anatomical differences in the corpus callosum have been found in various psychiatric disorders, but data on the genetic contributions to these differences have been limited. The current study used morphometric MRI data to assess the heritability of corpus callosum size and the genetic correlations among anatomical sub-regions of the corpus callosum among individuals with and without mood disorders. The corpus callosum (CC) was manually segmented at the mid-sagittal plane in 42 women (healthy, n = 14; major depressive disorder, n = 15; bipolar disorder, n = 13) and their 86 child or adolescent offspring. Four anatomical sub-regions (CC-genu, CC2, CC3 and CC-splenium) and total CC were measured and analyzed. Heritability and genetic correlations were estimated using a variance components method, with adjustment for age, sex, diagnosis, and diagnosis x age, where appropriate. Significant heritability was found for several CC sub-regions (P<0.01), with estimated values ranging from 48% (splenium) to 67% (total CC). There were strong and significant genetic correlations among most sub regions. Correlations between the genu and mid-body, between the genu and total corpus callosum, and between anterior and mid body were all >90%, but no significant genetic correlations were detected between ventral and rostral regions in this sample. Genetic factors play an important role in corpus callosum size among individuals. Distinct genetic factors seem to be involved in caudal and rostral regions, consistent with the divergent functional specialization of these brain areas.

Small vessel disease and memory loss: what the clinician needs to know to preserve patients' brain health

Small vessel disease (SVD) in the brain manifests in the periventricular and deep white matter and radiographically is described as "leukoaraiosis". It is increasingly recognized as a cause of morbidity from middle age onward and this clinical relevance has paralleled advances in the field of neuroradiology. Overall, SVD is a heterogenous group of vascular disorders that may be asymptomatic, or a harbinger of many conditions that jeopardize brain health. Management and prevention focuses on blood pressure control, lifestyle modification, and symptomatic treatment.

A Neuregulin-1 schizophrenia susceptibility variant causes perihippocampal fiber tract anomalies in healthy young subjects

BACKGROUND

Changes in fiber tract architecture have gained attention as a potentially important aspect of schizophrenia neuropathology. Although the exact pathogenesis of these abnormalities yet remains to be elucidated, a genetic component is highly likely. Neuregulin-1 (NRG1) is one of the best-validated schizophrenia susceptibility genes. We here report the impact of the Neuregulin-1 rs35753505 variant on white matter structure in healthy young individuals with no family history of psychosis.

METHODS

We compared fractional anisotropy in 54 subjects that were either homozygous for the risk C allele carriers (n = 31) for rs35753505 or homozygous for the T allele (n = 23) using diffusion tensor imaging with 3T. Tract-Based Spatial Statistics (TBSS), a method especially developed for diffusion data analysis, was used to improve white matter registration and to focus the statistical analysis to major fiber tracts.

RESULTS

Statistical analysis showed that homozygous risk C allele carriers featured elevated fractional anisotropy (FA) in the right perihippocampal region and the white matter proximate to the left area 4p as well as the right hemisphere of the cerebellum. We found three clusters of reduced FA values in homozygous C allele carriers: in the left superior parietal region, the right prefrontal white matter and in the deep white matter of the left frontal lobe.

CONCLUSION

Our results highlight the importance of Neuregulin-1 for structural connectivity of the right medial temporal lobe. This finding is in line with well known neuropathological findings in this region in patients with schizophrenia.

Different locations but common associations in subcortical hypodensities of presumed vascular origin: cross-sectional study on clinical and neurosonologic correlates

BACKGROUND

Subcortical hypodensities of presumed vascular etiology (SHPVO) are a clinical, radiological and neuropathological syndrome with a still largely unexplained pathophysiology. Parallel to the clinical heterogeneity, there is also recognised cerebral topographical diversity with undetermined etiological implications. Our aim is to assess clinical and neurosonological predictors of SHPVO according to their location.

METHODS

Cross sectional analysis of consecutive patients that underwent neurosonologic evaluation and head CT within one month, during a one year period. We excluded patients with absent temporal sonographic window, any pathology with a possible confounding effect on cerebral arterial pulsatility, atrial fibrillation and other etiologies of white matter diseases. The mean pulsatility index (PI) of both middle cerebral arteries was measured in the middle third of the M1 segment; intima media thickness was evaluated in the far wall of both common carotid arteries. SHPVO were rated by analysis of head CT in deep white matter (DWMH), periventricular white matter (PVWMH) and basal ganglia (BGH). We conducted a multivariate ordinal logistic regression model including all clinical, demographic and ultrasonographic characteristics to determine independent associations with SHPVO.

RESULTS

We included 439 patients, mean age 63.47 (SD: 14.94) years, 294 (67.0%) male. The independent predictors of SHPVO were age (OR = 1.067, 95% CI: 1.047-1.088, p < 0.001 for DWMH; OR = 1.068, 95% CI: 1.049-1.088, p < 0.001 for PVWMH; OR = 1.05, 95% CI: 1.03-1.071, p < 0.001 for BGH), hypertension (OR = 1.909, 95% CI: 1.222-2.981, p = 0.004 for DWMH; OR = 1.907, 95% CI: 1.238-2.938, p = 0.003 for PVWMH; OR = 1.775, 95% CI: 1.109-2.843, p = 0.017 for BGH) and PI (OR = 17.994, 95% CI: 6.875-47.1, p < 0.001 for DWMH; OR = 5.739, 95%CI: 2.288-14.397, p < 0.001 for PVWMH; OR = 11.844, 95% CI: 4.486-31.268, p < 0.001 for BGH) for all locations of SHPVO.

CONCLUSIONS

Age, hypertension and intracranial pulsatility are the main independent predictors of SHPVO across different topographic involvement and irrespective of extracranial atherosclerotic involvement.

Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging

The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.

Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging

The term cerebral small vessel disease (SVD) describes a range of neuroimaging, pathological, and associated clinical features. Clinical features range from none, to discrete focal neurological symptoms (eg, stroke), to insidious global neurological dysfunction and dementia. The burden on public health is substantial. The pathogenesis of SVD is largely unknown. Although the pathological processes leading to the arteriolar disease are associated with vascular risk factors and are believed to result from an intrinsic cerebral arteriolar occlusive disease, little is known about how these processes result in brain disease, how SVD lesions contribute to neurological or cognitive symptoms, and the association with risk factors. Pathology often shows end-stage disease, which makes identification of the earliest stages difficult. Neuroimaging provides considerable insights; although the small vessels are not easily seen themselves, the effects of their malfunction on the brain can be tracked with detailed brain imaging. We discuss potential mechanisms, detectable with neuroimaging, that might better fit the available evidence and provide testable hypotheses for future study.

Plasma lipidomic profile signature of hypertension in Mexican American families: specific role of diacylglycerols

Both as a component of metabolic syndrome and as an independent entity, hypertension poses a continued challenge with regard to its diagnosis, pathogenesis, and treatment. Previous studies have documented connections between hypertension and indicators of lipid metabolism. Novel technologies, such as plasma lipidomic profiling, promise a better understanding of disorders in which there is a derangement of the lipid metabolism. However, association of plasma lipidomic profiles with hypertension in a high-risk population, such as Mexican Americans, has not been evaluated before. Using the rich data and sample resource from the ongoing San Antonio Family Heart Study, we conducted plasma lipidomic profiling by combining high-performance liquid chromatography with tandem mass spectroscopy to characterize 319 lipid species in 1192 individuals from 42 large and extended Mexican American families. Robust statistical analyses using polygenic regression models, liability threshold models, and bivariate trait analyses implemented in the SOLAR software were conducted after accounting for obesity, insulin resistance, and relative abundance of various lipoprotein fractions. Diacylglycerols, in general, and the DG 16:0/22:5 and DG 16:0/22:6 lipid species, in particular, were significantly associated with systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP), as well as liability of incident hypertension measured during 7140.17 person-years of follow-up. Four lipid species, including the DG 16:0/22:5 and DG 16:0/22:6 species, showed significant genetic correlations with the liability of hypertension in bivariate trait analyses. Our results demonstrate the value of plasma lipidomic profiling in the context of hypertension and identify disturbance of diacylglycerol metabolism as an independent biomarker of hypertension.

Transcriptomics of cortical gray matter thickness decline during normal aging

INTRODUCTION

We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging.

METHODS

Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability.

RESULTS

Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT.

CONCLUSION

Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

Testing the hypothesis of accelerated cerebral white matter aging in schizophrenia and major depression

BACKGROUND

Elevated rate of aging-related biological and functional decline, termed "accelerated aging," is reported in patients with schizophrenia (SCZ) and major depressive disorder (MDD). We used diffusion tensor imaging derived fractional anisotropy (FA) as a biomarker of aging-related decline in white matter (WM) integrity to test the hypotheses of accelerated aging in SCZ and MDD.

METHODS

The SCZ cohort comprised 58 SCZ patients and 60 controls (aged 20-60 years). The MDD cohort comprised 136 MDD patients and 351 controls (aged 20-79 years). The main outcome measures were the diagnosis-by-age interaction on whole-brain-averaged WM FA values and FA values from 12 major WM tracts.

RESULTS

Diagnosis-by-age interaction for the whole-brain average FA was significant for the SCZ (p = .04) but not the MDD (p = .80) cohort. Diagnosis-by-age interaction was nominally significant (p<.05) for five WM tracts for SCZ and for none of the tracts in the MDD cohort. Tract-specific heterochronicity of the onset of age-related decline in SCZ demonstrated strong negative correlations with the age-of-peak myelination and the rates of age-related decline obtained from normative sample (r =-.61 and-.80, p<.05, respectively). No such trends existed for MDD cohort.

CONCLUSIONS

Cerebral WM showed accelerated aging in SCZ but not in MDD, suggesting some difference in the pathophysiology underlying their WM aging changes. Tract-specific heterochronicity of WM development modulated presentation of accelerated aging in SCZ: WM tracts that matured later in life appeared more sensitive to the pathophysiology of SCZ and demonstrated more susceptibility to disorder-related accelerated decline in FA values with age. This trend was not observed in MDD cohort.

The TWIN-E project in emotional wellbeing: study protocol and preliminary heritability results across four MRI and DTI measures

Despite the significant advancements being made in the neurogenetics for mental health, the identification and validation of potential endophenotype markers of risk and resilience remain to be confirmed. The TWIN-E study (The Twin study in Wellbeing using Integrative Neuroscience of Emotion) aims to validate endophenotype markers of mental health across cognitive, brain, and autonomic measures by testing the heritability, clinical plausibility, and reliability of each of these measures in a large adult twin cohort. The specific gene and environmental mechanisms that moderate prospective links between endophenotype-phenotype markers and the final outcome of wellbeing will also be identified. TWIN-E is a national prospective study with three phases: I) baseline testing on a battery of online questionnaires and cognitive tasks, and EEG, MRI, and autonomic testing; II) 12-month follow-up testing on the online assessments; and III) randomized controlled trial of brain training. Minimum target numbers include 1,500 male/female twins (18-65 years) for the online assessments (Phase I and II), 300 twins for the EEG testing component, and 244 twins for the MRI testing component. For Phase III, each twin out of the pair will be randomized to either the treatment or waitlist control group to test the effects of brain training on mental health over a 30-day period, and to confirm the gene-environment and endophenotype contributions to treatment response. Preliminary heritability results are provided for the first 50% of the MRI subgroup (n = 142) for the grey matter volume, thickness, and surface area measures, and white matter diffuse tensor imaging fractional anisotropy.

Bayesian methods for multivariate modeling of pleiotropic SNP associations and genetic risk prediction

Genome-wide association studies (GWAS) have identified numerous associations between genetic loci and individual phenotypes; however, relatively few GWAS have attempted to detect pleiotropic associations, in which loci are simultaneously associated with multiple distinct phenotypes. We show that pleiotropic associations can be directly modeled via the construction of simple Bayesian networks, and that these models can be applied to produce single or ensembles of Bayesian classifiers that leverage pleiotropy to improve genetic risk prediction. The proposed method includes two phases: (1) Bayesian model comparison, to identify Single-Nucleotide Polymorphisms (SNPs) associated with one or more traits; and (2) cross-validation feature selection, in which a final set of SNPs is selected to optimize prediction. To demonstrate the capabilities and limitations of the method, a total of 1600 case-control GWAS datasets with two dichotomous phenotypes were simulated under 16 scenarios, varying the association strengths of causal SNPs, the size of the discovery sets, the balance between cases and controls, and the number of pleiotropic causal SNPs. Across the 16 scenarios, prediction accuracy varied from 90 to 50%. In the 14 scenarios that included pleiotropically associated SNPs, the pleiotropic model search and prediction methods consistently outperformed the naive model search and prediction. In the two scenarios in which there were no true pleiotropic SNPs, the differences between the pleiotropic and naive model searches were minimal. To further evaluate the method on real data, a discovery set of 1071 sickle cell disease (SCD) patients was used to search for pleiotropic associations between cerebral vascular accidents and fetal hemoglobin level. Classification was performed on a smaller validation set of 352 SCD patients, and showed that the inclusion of pleiotropic SNPs may slightly improve prediction, although the difference was not statistically significant. The proposed method is robust, computationally efficient, and provides a powerful new approach for detecting and modeling pleiotropic disease loci.

P-selectin Expression Tracks Cerebral Atrophy in Mexican-Americans

Background and Purpose: We hypothesized that the P-selectin (SELP) gene, localized to a region on chromosome 1q24, pleiotropically contributes to increased blood pressure and cerebral atrophy. We tested this hypothesis by performing genetic correlation analyses for 13 mRNA gene expression measures from P-selectin and 11 other genes located in 1q24 region and three magnetic resonance imaging derived indices of cerebral integrity. Methods: The subject pool consisted of 369 (219F; aged 28–85, average = 47.1 ± 12.7 years) normally aging, community-dwelling members of large extended Mexican-American families. Genetic correlation analysis decomposed phenotypic correlation coefficients into genetic and environmental components among 13 leukocyte-based mRNA gene expressions and three whole-brain and regional measurements of cerebral integrity: cortical gray matter thickness, fractional anisotropy of cerebral white matter, and the volume of hyperintensive WM lesions. Results: From the 13 gene expressions, significant phenotypic correlations were only found for the P- and L-selectin expression levels. Increases in P-selectin expression levels tracked with decline in cerebral integrity while the opposite trend was observed for L-selectin expression. The correlations for the P-selectin expression were driven by shared genetic factors, while the correlations with L-selectin expression were due to shared environmental effects. Conclusion: This study demonstrated that P-selectin expression shared a significant variance with measurements of cerebral integrity and posits elevated P-selectin expression levels as a potential risk factor of hypertension-related cerebral atrophy.

A library of cortical morphology analysis tools to study development, aging and genetics of cerebral cortex

Sharing of analysis techniques and tools is among the main driving forces of modern neuroscience. We describe a library of tools developed to quantify global and regional differences in cortical anatomy in high resolution structural MR images. This library is distributed as a plug-in application for popular structural analysis software, BrainVisa (BV). It contains tools to measure global and regional gyrification, gray matter thickness and sulcal and gyral white matter spans. We provide a description of each tool and examples for several case studies to demonstrate their use. These examples show how the BV library was used to study cortical folding process during antenatal development and recapitulation of this process during cerebral aging. Further, the BV library was used to perform translation research in humans and non-human primates on the genetics of cerebral gyrification. This library, including source code and self-contained binaries for popular computer platforms, is available from the NIH-Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) resource ( http://www.nitrc.org/projects/brainvisa_ext ).