Genetic influences on brain asymmetry: A DTI study of 374 twins and siblings

Brain asymmetry, or the structural and functional specialization of each brain hemisphere, has fascinated neuroscientists for over a century. Even so, genetic and environmental factors that influence brain asymmetry are largely unknown. Diffusion tensor imaging (DTI) now allows asymmetry to be studied at a microscopic scale by examining differences in fiber characteristics across hemispheres rather than differences in structure shapes and volumes. Here we analyzed 4. Tesla DTI scans from 374 healthy adults, including 60 monozygotic twin pairs, 45 same-sex dizygotic pairs, and 164 mixed-sex DZ twins and their siblings; mean age: 24.4 years ± 1.9 SD). All DTI scans were nonlinearly aligned to a geometrically-symmetric, population-based image template. We computed voxel-wise maps of significant asymmetries (left/right differences) for common diffusion measures that reflect fiber integrity (fractional and geodesic anisotropy; FA, GA and mean diffusivity, MD). In quantitative genetic models computed from all same-sex twin pairs (N=210 subjects), genetic factors accounted for 33% of the variance in asymmetry for the inferior fronto-occipital fasciculus, 37% for the anterior thalamic radiation, and 20% for the forceps major and uncinate fasciculus (all L > R). Shared environmental factors accounted for around 15% of the variance in asymmetry for the cortico-spinal tract (R > L) and about 10% for the forceps minor (L > R). Sex differences in asymmetry (men > women) were significant, and were greatest in regions with prominent FA asymmetries. These maps identify heritable DTI-derived features, and may empower genome-wide searches for genetic polymorphisms that influence brain asymmetry.

A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

Genetic influences on sulcal patterns of the brain

We present a shape-space approach for analyzing genetic influences on the shapes of the sulcal folding patterns on the cortex. Sulci are represented as continuously parameterized functions in a shape space, and shape differences between sulci are obtained via geodesics between them. The resulting statistical shape analysis framework is used not only to construct populations averages, but also used to compute meaningful correlations within and across groups of sulcal shapes. More importantly, we present a new algorithm that extends the traditional Euclidean estimate of the intra-class correlation to the geometric shape space, thereby allowing us to study heritability of sulcal shape traits for a population of 193 twin pairs. This new methodology reveals strong genetic influences on the sulcal geometry of the cortex.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Predicting white matter integrity from multiple common genetic variants

Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Genetic architecture of subcortical brain regions: Common and region-specific genetic contributions

Understanding the aetiology of patterns of variation within and covariation across brain regions is key to advancing our understanding of the functional, anatomical and developmental networks of the brain. Here we applied multivariate twin modelling and principal component analysis (PCA) to investigate the genetic architecture of the size of seven subcortical regions (caudate nucleus, thalamus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens) in a genetically informative sample of adolescents and young adults (N=1038; mean age=21.6±3.2years; including 148 monozygotic and 202 dizygotic twin pairs) from the Queensland Twin IMaging (QTIM) study. Our multivariate twin modelling identified a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In addition, we also found substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52). This provides further insight into the extent and organization of subcortical genetic architecture, which includes developmental and general growth pathways, as well as the functional specialization and maturation trajectories that influence each subcortical region. This multivariate twin study identifies a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In parallel, it also describes substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52).

A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: Replication in elderly and young populations

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

Effects of cold water immersion and active recovery on hemodynamics and recovery of muscle strength following resistance exercise

Cold water immersion (CWI) and active recovery (ACT) are frequently used as post-exercise recovery strategies. However, the physiological effects of CWI and ACT after resistance exercise are not well characterized. We examined the effects of CWI and ACT on cardiac output (Q), muscle oxygenation (SmO2) and blood volume (tHb), muscle temperature (Tmuscle ) and isometric strength after resistance exercise. On separate days, 10 men performed resistance exercise, followed by 10 min CWI at 10°C or 10 min ACT (low-intensity cycling). Q (7.9±2.7 l) and Tmuscle (2.2±0.8ºC) increased, whereas SmO2 (-21.5±8.8%) and tHb (-10.1±7.7 μM) decreased after exercise (p<0.05). During CWI, Q ̇(-1.1±0.7 l) and Tmuscle (-6.6±5.3ºC) decreased, while tHb (121±77 μM) increased (p<0.05). In the hour after CWI, Q ̇and Tmuscle remained low, while tHb also decreased (p<0.05). By contrast, during ACT, Q ̇(3.9±2.3 l), Tmuscle (2.2±0.5ºC), SmO2 (17.1±5.7%) and tHb (91±66 μM) all increased (p<0.05). In the hour after ACT, Tmuscle and tHb remained high (p<0.05). Peak isometric strength during 10 s maximum voluntary contractions (MVCs) did not change significantly after CWI, whereas it decreased after ACT (-30 to -45 Nm; p<0.05). Muscle deoxygenation time during MVCs increased after ACT (p<0.05), but not after CWI. Muscle reoxygenation time after MVCs tended to increase after CWI (p=0.052). These findings suggest firstly that hemodynamics and muscle temperature after resistance exercise are dependent on ambient temperature and metabolic demands with skeletal muscle, and secondly, that recovery of strength after resistance exercise is independent of changes in hemodynamics and muscle temperature.

Genetic structure of invasive weed Parthenium hysterophorus in Australia and Pakistan

Understanding the patterns of genetic structure in the introduced range of invasive species can help elucidate invasion histories and levels of gene flow among populations. Parthenium weed (Parthenium hysterophorus L.; PW) is native to the Gulf of Mexico and central South America but has become globally invasive during the last three decades and little is known about the genetics of this species in its invasive range. The present study was conducted to determine the genetic structure of 95 individual samples from 11 populations (9 from Pakistan and 2 from Australia) of PW using ISSR fingerprinting. A total of 30 ISSR primers were screened; of which eight were selected due to their high polymorphism and reproducibility. In toto 147 bands were amplified, which ranged in size from 200-2000 bp; among which 97 were polymorphic. Genetic diversity within the populations both from Pakistan and Australia ranged between 0.193-0.278. Approximately 18% of genetic variation occurred among and 82% within populations. Principal Coordinate Analysis showed that within the 95 samples two groups were present: one contained samples collected mainly from Pakistan and the second group included the Australian samples along with two populations from Pakistan. Overall, there was limited gene flow among PW populations in Pakistan, although the genetic diversity within populations was high. The degree of genetic variation inferred from various population diversity measures can predict different events of founding populations, which have passed through complicated processes of invasion, experiencing genetic bottlenecks. Taken together, results showed that PW in Pakistan is genetically heterogeneous and may have been the result of multiple introductions.

Knowledge sharing success and resistance in an engineering department: A case study

The centrality of knowledge sharing to organizations’ sustainability has been established. This research explores and illustrates the influences for individual professionals and paraprofessionals – specifically civil engineers and design drafters – to share their deep, personally constructed knowledge, in a public sector provider of railways infrastructure. It investigates the extent to which: (i) knowledge sharing will be positively influenced by the professional identity, values and knowledge culture to achieve organizational and project goals, and; (ii) sharing of deep personal expertise will be influenced by the quality of relational capital among individuals and individual perspectives. It finds that knowledge sharing develops within frameworks established through the alignment among sector, profession and organization values. However, individual behavior is found to be most strongly influenced by the presence and quality of relational capital and individuals’ personal perspectives.

Effects of compression on lymphoedema during resistance exercise in women with breast cancer-related lymphoedema: A randomised, cross-over trial

Background The use of compression garments during exercise is recommended for women with breast cancer-related lymphoedema, but the evidence behind this clinical recommendation is unclear. The aim of this randomised, cross-over trial was to compare the acute effects of wearing versus not wearing compression during a single bout of moderate-load resistance exercise on lymphoedema status and its associated symptoms in women with breast cancer-related lymphoedema. Methods Twenty-five women with clinically diagnosed, stable unilateral breast cancer-related lymphoedema completed two resistance exercise sessions, one with compression and one without, in a randomised order separated by a 14 day wash-out period. The resistance exercise session consisted of six upper-body exercises, with each exercise performed for three sets at a moderate-load (10-12 repetition maximum). Primary outcome was lymphoedema, assessed using bioimpedance spectroscopy (L-Dex score). Secondary outcomes were lymphoedema as assessed by arm circumferences (percent inter-limb difference and sum-of-circumferences), and symptom severity for pain, heaviness and tightness, measured using visual analogue scales. Measurements were taken pre-, immediately post- and 24 hours post-exercise. Results There was no difference in lymphoedema status (i.e., L-Dex scores) pre- and post-exercise sessions or between the compression and non-compression condition [Mean (SD) for compression pre-, immediately post- and 24 hours post-exercise: 17.7 (21.5), 12.7 (16.2) and 14.1 (16.7), respectively; no compression: 15.3 (18.3), 15.3 (17.8), and 13.4 (16.1), respectively]. Circumference values and symptom severity were stable across time and treatment condition. Conclusions An acute bout of moderate-load, upper-body resistance exercise performed in the absence of compression does not exacerbate lymphoedema in women with breast cancer-related lymphoedema.

Resistance exercise with low glycogen increases p53 phosphorylation and PGC-1α mRNA in skeletal muscle

Purpose We determined the effect of reduced muscle glycogen availability on cellular pathways regulating mitochondrial biogenesis and substrate utilization after a bout of resistance exercise. Methods Eight young, recreationally trained men undertook a glycogen depletion protocol of one-leg cycling to fatigue (LOW), while the contralateral (control) leg rested (CONT). Following an overnight fast, subjects completed 8 sets of 5 unilateral leg press repetitions (REX) at 80 % 1 Repetition Maximum (1RM) on each leg. Subjects consumed 500 mL protein/CHO beverage (20 g whey + 40 g maltodextrin) upon completion of REX and 2 h later. Muscle biopsies were obtained at rest and 1 and 4 h after REX in both legs. Results Resting muscle glycogen was higher in the CONT than LOW leg (~384 ± 114 vs 184 ± 36 mmol kg−1 dry wt; P < 0.05), and 1 h and 4 h post-exercise (P < 0.05). Phosphorylation of p53Ser15 increased 1 h post-exercise in LOW (~115 %, P < 0.05) and was higher than CONT at this time point (~87 %, P < 0.05). p38MAPKThr180/Tyr182 phosphorylation increased 1 h post-exercise in both CONT and LOW (~800–900 %; P < 0.05) but remained above rest at 4 h only in CONT (~585 %, P < 0.05; different between legs P < 0.05). Peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) mRNA was elevated 4 h post-exercise in LOW (~200 %, P < 0.05; different between legs P < 0.05). There were no changes in Fibronectin type III domain-containing protein 5 (FNDC5) mRNA for CONT or LOW legs post-exercise. Conclusion Undertaking resistance exercise with low glycogen availability may enhance mitochondrial-related adaptations through p53 and PGC-1α-mediated signalling.