Affective Science Research: Perspectives and Priorities from the National Institutes of Health.

Affective science is a broad and burgeoning field, and the National Institutes of Health (NIH) support research on a similarly broad range of topics. Across NIH, funding is available for basic, translational, and intervention research, including research in non-human animals, healthy populations, and those with or at risk for disease. Multiple NIH Institutes and Centers have specific programs devoted to topics within the affective science umbrella. Here, we introduce the funding priorities of these six: the National Cancer Institute (NCI), National Center for Complementary and Integrative Health (NCCIH), National Institute of Mental Health (NIMH), National Institute on Aging (NIA), National Institute on Drug Abuse (NIDA), and National Institute on Minority Health and Health Disparities (NIMHD). We then discuss overlapping themes and offer a perspective on promising research directions.

Differential predictors for alcohol use in adolescents as a function of familial risk.

Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions.

Association between childhood trauma and risk for obesity: a putative neurocognitive developmental pathway.

BACKGROUND: Childhood trauma increases the risk for adult obesity through multiple complex pathways, and the neural substrates are yet to be determined. METHODS: Participants from three population-based neuroimaging cohorts, including the IMAGEN cohort, the UK Biobank (UKB), and the Human Connectome Project (HCP), were recruited. Voxel-based morphometry analysis of both childhood trauma and body mass index (BMI) was performed in the longitudinal IMAGEN cohort; validation of the findings was performed in the UKB. White-matter connectivity analysis was conducted to study the structural connectivity between the identified brain region and subdivisions of the hypothalamus in the HCP. RESULTS: In IMAGEN, a smaller frontopolar cortex (FPC) was associated with both childhood abuse (CA) (ß = - .568, 95%CI - .942 to - .194; p = .003) and higher BMI (ß = - .086, 95%CI - .128 to - .043; p < .001) in male participants, and these findings were validated in UKB. Across seven data collection sites, a stronger negative CA-FPC association was correlated with a higher positive CA-BMI association (ß = - 1.033, 95%CI - 1.762 to - .305; p = .015). Using 7-T diffusion tensor imaging data (n = 156), we found that FPC was the third most connected cortical area with the hypothalamus, especially the lateral hypothalamus. A smaller FPC at age 14 contributed to higher BMI at age 19 in those male participants with a history of CA, and the CA-FPC interaction enabled a model at age 14 to account for some future weight gain during a 5-year follow-up (variance explained 5.8%). CONCLUSIONS: The findings highlight that a malfunctioning, top-down cognitive or behavioral control system, independent of genetic predisposition, putatively contributes to excessive weight gain in a particularly vulnerable population, and may inform treatment approaches.

Cortical Surfaces Mediate the Relationship Between Polygenic Scores for Intelligence and General Intelligence.

Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2-94.3; P < 0.005), and up to 3.0% in IntegraMooDS (F1,725 = 10.0-21.0; P < 0.005). The association between polygenic scores and g-factor was partially mediated by SA and CT in prefrontal, anterior cingulate, insula, and medial temporal cortices in both samples (PFWER-corrected < 0.005). The variance explained by mediation was up to 0.75% in IMAGEN and 0.77% in IntegraMooDS. Our results provide evidence that cumulative genetic load influences g-factor via cortical structure. The consistency of our results across samples suggests that cortex morphology could be a novel potential biomarker for neurocognitive dysfunction that is among the most intractable psychiatric symptoms.

COMT Val158Met Polymorphism and Social Impairment Interactively Affect Attention-Deficit Hyperactivity Symptoms in Healthy Adolescents.

The dopaminergic system has been shown to have substantial effects on the etiology of attention-deficit hyperactivity disorder (ADHD). However, while some studies found a significant direct effect, others did not. In this context, social behavior might play an important role as a factor that is related both to the dopaminergic system and ADHD. In a large epidemiological sample of adolescents (N = 462; 16-17 years), we assessed the level of ADHD symptoms using the Strengths and Difficulties Questionnaire, social behavior using the Social Responsiveness Scale, and the allelic distribution of the dopaminergic catechol-O-methyltransferase (COMT) Val158Met polymorphism. We found a significant association between COMT and social impairment, insofar as Met-allele carriers showed increased levels of social impairment. Moreover, social impairment significantly determined an association between COMT and ADHD (explained variance: 19.09%). This effect did not significantly differ between males and females. COMT and social impairment might interactively affect ADHD symptomatology, and could thus represent significant gene-phenotypic risk factors for ADHD symptomatology. This might have interesting implications for prevention and intervention strategies with a focus on social behavior in genetically at-risk individuals.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Neuroimaging Identifies Patients Most Likely to Respond to a Restorative Stroke Therapy.

BACKGROUND AND PURPOSE: Patient heterogeneity reduces statistical power in clinical trials of restorative therapies. Valid predictors of treatment responsiveness are needed, and several have been studied with a focus on corticospinal tract (CST) injury. We studied performance of 4 such measures for predicting behavioral gains in response to motor training therapy. METHODS: Patients with subacute-chronic hemiparetic stroke (n=47) received standardized arm motor therapy, and change in arm Fugl-Meyer score was calculated from baseline to 1 month post-therapy. Injury measures calculated from baseline magnetic resonance imaging included (1) percent CST overlap with stroke, (2) CST-related atrophy (cerebral peduncle area), (3) CST integrity (fractional anisotropy) in the cerebral peduncle, and (4) CST integrity in the posterior limb of internal capsule. RESULTS: Percent CST overlap with stroke, CST-related atrophy, and CST integrity did not correlate with one another, indicating that these 3 measures captured independent features of CST injury. Percent injury to CST significantly predicted treatment-related behavioral gains (r=-0.41; P=0.004). The other CST injury measures did not, neither did total infarct volume nor baseline behavioral deficits. When directly comparing patients with mild versus severe injury using the percent CST injury measure, the odds ratio was 15.0 (95% confidence interval, 1.54-147; P<0.005) for deriving clinically important treatment-related gains. CONCLUSIONS: Percent CST injury is useful for predicting motor gains in response to therapy in the setting of subacute-chronic stroke. This measure can be used as an entry criterion or a stratifying variable in restorative stroke trials to increase statistical power, reduce sample size, and reduce the cost of such trials.

Mouse and Human Genetic Analyses Associate Kalirin with Ventral Striatal Activation during Impulsivity and with Alcohol Misuse.

Impulsivity is associated with a spectrum of psychiatric disorders including drug addiction. To investigate genetic associations with impulsivity and initiation of drug taking, we took a two-step approach. First, we identified genes whose expression level in prefrontal cortex, striatum and accumbens were associated with impulsive behavior in the 5-choice serial reaction time task across 10 BXD recombinant inbred (BXD RI) mouse strains and their progenitor C57BL/6J and DBA2/J strains. Behavioral data were correlated with regional gene expression using GeneNetwork (www.genenetwork.org), to identify 44 genes whose probability of association with impulsivity exceeded a false discovery rate of < 0.05. We then interrogated the IMAGEN database of 1423 adolescents for potential associations of SNPs in human homologs of those genes identified in the mouse study, with brain activation during impulsive performance in the Monetary Incentive Delay task, and with novelty seeking scores from the Temperament and Character Inventory, as well as alcohol experience. There was a significant overall association between the human homologs of impulsivity-related genes and percentage of premature responses in the MID task and with fMRI BOLD-response in ventral striatum (VS) during reward anticipation. In contrast, no significant association was found between the polygenic scores and anterior cingulate cortex activation. Univariate association analyses revealed that the G allele (major) of the intronic SNP rs6438839 in the KALRN gene was significantly associated with increased VS activation. Additionally, the A-allele (minor) of KALRN intronic SNP rs4634050, belonging to the same haplotype block, was associated with increased frequency of binge drinking.

Understanding the Impact of Stroke on Brain Motor Function: A Hierarchical Bayesian Approach.

Stroke is a disturbance in blood supply to the brain resulting in the loss of brain functions, particularly motor function. A study was conducted by the UCI Neurorehabilitation Lab to investigate the impact of stroke on motor-related brain regions. Functional MRI (fMRI) data were collected from stroke patients and healthy controls while the subjects performed a simple motor task. In addition to affecting local neuronal activation strength, stroke might also alter communications (i.e., connectivity) between brain regions. We develop a hierarchical Bayesian modeling approach for the analysis of multi-subject fMRI data that allows us to explore brain changes due to stroke. Our approach simultaneously estimates activation and condition-specific connectivity at the group level, and provides estimates for region/subject-specific hemodynamic response functions. Moreover, our model uses spike and slab priors to allow for direct posterior inference on the connectivity network. Our results indicate that motor-control regions show greater activation in the unaffected hemisphere and the midline surface in stroke patients than those same regions in healthy controls during the simple motor task. We also note increased connectivity within secondary motor regions in stroke subjects. These findings provide insight into altered neural correlates of movement in subjects who suffered a stroke.

BDNF Val66Met Polymorphism Is Related to Motor System Function After Stroke.

BACKGROUND: The val(66)met polymorphism in brain-derived neurotrophic factor (BDNF) has been associated with poorer outcomes after stroke. The mechanism for this finding remains uncertain but might be related to the reduced motor system activation associated with this polymorphism in healthy people. OBJECTIVE: The current study examined whether the presence of the BDNF val(66)met polymorphism is associated with reduced motor system activation after stroke. DESIGN AND METHODS: Forty-two patients with stroke who were enrolled in 1 of 2 studies of robot-assisted arm motor therapy participated in the study. All participants were tested for the BDNF val(66)met polymorphism followed by functional magnetic resonance imaging during affected hand movement. RESULTS: Participants averaged 12 months poststroke and had wide-ranging motor deficits (Fugl-Meyer scale scores=14-60). Brain activation in participants without the BDNF val(66)met polymorphism (n=26) spanned bilateral motor networks with a larger volume (total=334 cc) than that found in participants with this polymorphism (n=16) (97 cc). Regional analyses were consistent. Participants without this polymorphism showed larger ipsilesional primary sensorimotor cortex activation volume and magnitude compared with those in whom the polymorphism was present. LIMITATIONS: The extent to which these findings generalize to other populations of people with stroke, such as those with stroke <7 days prior, remains uncertain. CONCLUSIONS: Functional magnetic resonance imaging during affected hand movement showed decreased brain activation among participants with the BDNF val(66)met polymorphism compared with those lacking this polymorphism, especially in the ipsilesional primary sensorimotor cortex contralateral to movement. These results echo findings in healthy people and suggest that genetic factors affecting the normal brain continue to be operative after stroke. The findings suggest a potential imaging-based endophenotype for the BDNF val(66)met polymorphism's effect on the motor system that may be useful in a clinical trial setting.