Comparing empirical kinship derived heritability for imaging genetics traits in the UK biobank and human connectome project

Imaging genetics analyses use neuroimaging traits as intermediate phenotypes to infer the degree of genetic contribution to brain structure and function in health and/or illness. Coefficients of relatedness (CR) summarize the degree of genetic similarity among subjects and are used to estimate the heritability – the proportion of phenotypic variance explained by genetic factors. The CR can be inferred directly from genome-wide genotype data to explain the degree of shared variation in common genetic polymorphisms (SNP-heritability) among related or unrelated subjects. We developed a central processing and graphics processing unit (CPU and GPU) accelerated Fast and Powerful Heritability Inference (FPHI) approach that linearizes likelihood calculations to overcome the ∼N2–3 computational effort dependency on sample size of classical likelihood approaches. We calculated for 60 regional and 1.3 × 105 voxel-wise traits in N = 1,206 twin and sibling participants from the Human Connectome Project (HCP) (550 M/656 F, age = 28.8 ± 3.7 years) and N = 37,432 (17,531 M/19,901 F; age = 63.7 ± 7.5 years) participants from the UK Biobank (UKBB). The FPHI estimates were in excellent agreement with heritability values calculated using Genome-wide Complex Trait Analysis software (r = 0.96 and 0.98 in HCP and UKBB sample) while significantly reducing computational (102–4 times). The regional and voxel-wise traits heritability estimates for the HCP and UKBB were likewise in excellent agreement (r = 0.63–0.76, p \u3c 10−10). In summary, the hardware-accelerated FPHI made it practical to calculate heritability values for voxel-wise neuroimaging traits, even in very large samples such as the UKBB. The patterns of additive genetic variance in neuroimaging traits measured in a large sample of related and unrelated individuals showed excellent agreement regardless of the estimation method. The code and instruction to execute these analyses are available at www.solar-eclipse-genetics.org

Mapping local and long-distance resting connectivity markers of TMS-related inhibition reduction in schizophrenia

Short interval intracortical inhibition (SICI) is a biomarker for altered motor inhibition in schizophrenia, but the manner in which distant sites influence the inhibitory cortical-effector response remains elusive. Our study investigated local and long-distance resting state functional connectivity (rsFC) markers of SICI in a sample of N = 23 patients with schizophrenia and N = 29 controls. Local functional connectivity was quantified using regional homogeneity (ReHo) analysis and long-range connectivity was estimated using seed-based rsFC analysis. Direct and indirect effects of connectivity measures on SICI were modeled using mediation analysis. Higher SICI ratios (indicating reduced inhibition) in patients were associated with lower ReHo in the right insula. Follow-up rsFC analyses showed that higher SICI scores (indicating reduced inhibition) were associated with reduced connectivity between right insula and hubs of the corticospinal pathway: sensorimotor cortex and basal ganglia. Mediation analysis supported a model in which the direct effect of local insular connectivity strength on SICI is mediated by the interhemispheric connectivity between insula and left sensorimotor cortex. The broader clinical implications of these findings are discussed with emphasis on how these preliminary findings might inform novel interventions designed to restore or improve SICI in schizophrenia and deepen our understanding of motor inhibitory control and impact of abnormal signaling in motor-inhibitory pathways in schizophrenia

Differential Modulation of Synaptic Strength and Timing Regulate Synaptic Efficacy in a Motor Network

Neuromodulators modify network output by altering neuronal firing properties and synaptic strength at multiple sites; however, the functional importance of each site is often unclear. We determined the importance of monoamine modulation of a single synapse for regulation of network cycle frequency in the oscillatory pyloric network of the lobster. The pacemaker kernel of the pyloric network receives only one chemical synaptic feedback, an inhibitory synapse from the lateral pyloric (LP) neuron to the pyloric dilator (PD) neurons, which can limit cycle frequency. We measured the effects of dopamine (DA), octopamine (Oct), and serotonin (5HT) on the strength of the LP→PD synapse and the ability of the modified synapse to regulate pyloric cycle frequency. DA and Oct strengthened, whereas 5HT weakened, LP→PD inhibition. Surprisingly, the DA-strengthened LP→PD synapse lost its ability to slow the pyloric oscillations, whereas the 5HT-weakened LP→PD synapse gained a greater influence on the oscillations. These results are explained by monoamine modulation of factors that determine the firing phase of the LP neuron in each cycle. DA acts via multiple mechanisms to phase-advance the LP neuron into the pacemaker's refractory period, where the strengthened synapse has little effect. In contrast, 5HT phase-delays LP activity into a region of greater pacemaker sensitivity to LP synaptic input. Only Oct enhanced LP regulation of cycle period simply by enhancing LP→PD synaptic strength. These results show that modulation of the strength and timing of a synaptic input can differentially affect the synapse's efficacy in the network

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 ) and CMD (F = 24.69, p = 6.82 × 10 ) significantly, independently impacted whole-brain QRI in SMI+. SSD had the largest effect (Cohen\u27s 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 \u3c 10 ) 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 \u3c 10 ). 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

Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity

Regional homogeneity (ReHo) is a measure of local functional brain connectivity that has been reported to be altered in a wide range of neuropsychiatric disorders. Computed from brain resting-state functional MRI time series, ReHo is also sensitive to fluctuations in cerebral blood flow (CBF) that in turn may be influenced by cerebrovascular health. We accessed cerebrovascular health with Framingham cardiovascular risk score (FCVRS). We hypothesize that ReHo signal may be influenced by regional CBF; and that these associations can be summarized as FCVRS→CBF→ReHo. We used three independent samples to test this hypothesis. A test-retest sample of N = 30 healthy volunteers was used for test-retest evaluation of CBF effects on ReHo. Amish Connectome Project (ACP) sample (N = 204, healthy individuals) was used to evaluate association between FCVRS and ReHo and testing if the association diminishes given CBF. The UKBB sample (N = 6,285, healthy participants) was used to replicate the effects of FCVRS on ReHo. We observed strong CBF→ReHo links (p<2.5 × 10−3) using a three-point longitudinal sample. In ACP sample, marginal and partial correlations analyses demonstrated that both CBF and FCVRS were significantly correlated with the whole-brain average (p<10−6) and regional ReHo values, with the strongest correlations observed in frontal, parietal, and temporal areas. Yet, the association between ReHo and FCVRS became insignificant once the effect of CBF was accounted for. In contrast, CBF→ReHo remained significantly linked after adjusting for FCVRS and demographic covariates (p<10−6). Analysis in N = 6,285 replicated the FCVRS→ReHo effect (p = 2.7 × 10−27). In summary, ReHo alterations in health and neuropsychiatric illnesses may be partially driven by region-specific variability in CBF, which is, in turn, influenced by cardiovascular factors