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Crow, S.

Publications and source records attributed to Crow, S..

3 recordsLinked to original sources

Using HD-DOT in precision accuracy microgenetic research designs to measure change over time in speech, language, and hearing clinical populations

Documenting change is fundamental to understanding the process of intervention among individuals with communication disorders. This technical report demonstrates the clinical applicability of wearable fNIRS systems and the NeuroDOT processing pipelines for examining within-person cortical dynamics of learning. Using a microgenetic research design and a dense sampling approach, we examined changes in the prefrontal cortical hemodynamic response in an adult female participant who completed the same spoken sentence repetition and auditory fixation tasks across eight sessions. In addition to behavioral accuracy, hemodynamic data were collected with a continuous-wave, multi-channel fNIRS system (NIRSport2) using a prefrontal 20-channel optode montage. Data were processed using NeuroDOT (https://www.nitrc.org/projects/neurodot) (Eggebrecht & Culver, 2019) to: (i) standardize signal quality across the sessions to quantify motion levels and to ensure standardized brain map specificity, (ii) to examine both channel space fluctuations in the hemodynamic response and map changes in cortical activation patterns over the sessions. The signal quality met the predefined criteria for only the first five sessions. Participants repetition accuracy did not improve over the five sessions. Channel-wise analysis revealed that HbO concentration differs significantly over right and left hemisphere channels over the course of the five sessions for the Sentence Repetition task, but not for the Auditory Fixation condition. Brain maps revealed qualitative differences in the pattern of prefrontal cortical activation across the five sessions. Behavioral assessments do not fully capture what occurs during speech repetition tasks, and leveraging neuroimaging can help identify and discriminate between disordered and neurotypical populations.

neuroscience↗

Shared Genetic Risk between Eating Disorder- and Substance-Use-Related Phenotypes: Evidence from Genome-Wide Association Studies

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; q<0.0001), and cannabis initiation and AN with binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to -0.23; qs<0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships between these behaviors.

genetics↗

Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations

Anorexia nervosa (AN) is a serious eating disorder characterized by restriction of energy intake relative to requirements, resulting in abnormally low body weight. It has a lifetime prevalence of approximately 1%, disproportionately affects females1,2, and has no well replicated evidence of effective pharmacological or psychological treatments despite high morbidity and mortality2. Twin studies support a genetic basis for the observed aggregation of AN in families3, with heritability estimates of 48%-74%4. Although initial genome-wide association studies (GWASs) were underpowered5,6, evidence suggested that signals for AN would be detected with increased power5. We present a GWAS of 3,495 AN cases and 10,982 controls with one genome-wide significant locus (index variant rs4622308, p=4.3x10-9) in a region (chr12:56,372,585-56,482,185) which includes six genes. The SNP-chip heritability [Formula] of AN from these data is 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability stems from common genetic variation. Using these GWAS results, we also find significant positive genetic correlations with schizophrenia, neuroticism, educational attainment, and HDL cholesterol, and significant negative genetic correlations with body mass, insulin, glucose, and lipid phenotypes. Our results support the reconceptualization of AN as a disorder with both psychiatric and metabolic components.

genomics↗