Translational insights into the genetic etiology of mental health disorders: Examining risk factor models, neuroimaging, and current dissemination practices

Psychiatric genetics is a basic science field that has potential for practical application and effective translation. To date, translational frameworks utilized by this field have been linear (e.g., sequential) in nature, focusing on molecular genetic information. It is proposed that non-linear (e.g., socio-ecological) frameworks are a better way to immediately translate non-molecular genetic information. This dissertation explored the translation of psychiatric genetic information in two ways. First, a survey was sent to academic stakeholders to assess the state of the science regarding the translation of genetic information to the clinical care of mental health disorders. Findings from this indicate a translation-genetic competence gap whereby genetic knowledge reinforces linear frameworks and genetic competence is needed to achieve effective translation in this content area. Second, a new risk factor model for social anxiety was created that incorporated genetic, environmental, and neurophysiological risk factors (behavioral inhibition, parental bonding, emotion reactivity). Findings indicate that genetic etiology is more informative knowledge that can influence risk factor models and possibly prevention and intervention efforts for social anxiety. Overall this dissertation paves the way for examining the translational capacity of psychiatric genetics in a clinical setting. It constitutes the first examination of barriers to and a potential solution for the most effective translation of psychiatric genetic information

Proof of concept of a personalized genetic risk tool to promote smoking cessation:High acceptability and reduced cigarette smoking

Relatively little is known about the possible effects of personalized genetic risk information on smoking, the leading preventable cause of morbidity and mortality. We examined the acceptability and potential behavior change associated with a personalized genetically-informed risk tool (RiskProfile) among current smokers. Current smokers (n=108) were enrolled in a pre-post study with three visits. At Visit 1, participants completed a baseline assessment and genetic testing via 23andMe. Participants’ raw genetic data (CHRNA5 variants) and smoking heaviness were used to create a tailored RiskProfile tool that communicated personalized risks of smoking-related diseases and evidence-based recommendations to promote cessation. Participants received their personalized RiskProfile intervention at Visit 2, approximately 6 weeks later. Visit 3 involved a telephone-based follow-up assessment 30 days after intervention. Of enrolled participants, 83% were retained across the three visits. Immediately following intervention, acceptability of RiskProfile was high (M=4.4; SD=0.6 on scale of 1 to 5); at 30-day follow-up, 89% of participants demonstrated accurate recall of key intervention messages. In the full analysis set of this single-arm trial, cigarettes smoked per day decreased from intervention to 30-day follow-up [11.3 vs. 9.8, difference=1.5, 95% CI (0.6—2.4), p=.001]. A personalized genetically-informed risk tool was found to be highly acceptable and associated with a reduction in smoking, although the absence of a control group must be addressed in future research. This study demonstrates proof of concept for translating key basic science findings into a genetically-informed risk tool that was used to promote progress toward smoking cessation

Characterization of Service Use for Alcohol Problems Across Generations and Sex in Adults With Alcohol Use Disorder

Background: There are gaps in the literature on service use (help-seeking and treatment utilization) for alcohol problems among those with alcohol use disorder (AUD). First, policy changes and cultural shifts (e.g., insurance) related to AUD have occurred over the last few decades, making it important to study generational differences. Second, multiple studies have found that females receive fewer services than males, and exploring whether these sex differences persist across generations can inform public health and research endeavors. The current study examined service use for alcohol problems among individuals with AUD. The aims were as follows: (i) to describe service use for alcohol problems; (ii) to assess generational differences (silent [b. 1928 to 1945], boomer [b. 1946 to 1964], generation X [b. 1965 to 1980], millennial [b. 1981 to 1996]) in help-seeking and treatment utilization; and (iii) to examine sex differences across generations. Methods: Data were from affected family members of probands who participated in the Collaborative Study on the Genetics of Alcoholism (N = 4,405). First, frequencies for service use variables were calculated across generations. Pearson chi-square and ANOVA were used to test for differences in rates and types of service use across generations, taking familial clustering into account. Next, Cox survival modeling was used to assess associations of generation and sex with time to first help-seeking and first treatment for AUD, and time from first onset of AUD to first help-seeking and first treatment. Interactions between generation and sex were tested within each Cox regression. Results: Significant hazards were found in all 4 transitions. Overall, younger generations used services earlier than older generations, which translated into higher likelihoods of these behaviors. Regardless of generation, younger females were less likely to use services than males. Conclusions: There are generational and sex differences in service use for alcohol problems among individuals with AUD. Policy and clinical implications are discussed

Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

Abstract: Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

An Implementation Approach to Translating Assessment Data into Treatment for Disorders of Addiction

Effective translation of data to inform real-time patient care is lacking in addiction inpatient settings. The current study presents the optimization of an assessment report that is used by clinicians to individualize treatment. A multi-aim, iterative approach was taken, utilizing an implementation science perspective to arrive at a final version of the assessment report. This occurred at a small inpatient addiction treatment facility. Participants were all available clinical staff (N = 7; female = 71%). A quantitative survey was used for aims 1 and 2 to, respectively, assess motives and context around the report as well as evaluate its design. Aim 3 focused on optimization via semi-structured interviews. Descriptive and modified content analyses were utilized appropriately across aims. This resulted in five versions of the assessment report being created between February 2021 and August 2022, the most recent of which was adapted into patients’ electronic medical records. We discuss each version of the report in depth, including clinicians’ iterative feedback and researchers’ perceived barriers to this translational process. The response rate was 64.3%. The current study highlights a replicable approach for optimizing the translation of assessment data into treatment for patients with disorders of addiction as well as an assessment report that could be utilized by similar facilities with a naturally low sample size

Resting Heart Rate Variability (HRV) in Adolescents and Young Adults from a Genetically-Informed Perspective

Reduced heart rate variability (HRV) is associated with cardiac morbidity, mortality, and negative psychopathology. Most research concerning genetic influences on HRV has focused on adult populations, with fewer studies investigating the developmental period of adolescence and emerging adulthood. The current study estimated the genetic and environmental contributions to resting HRV in a sample of twins using various HRV time domain metrics to assess autonomic function across two different time measurement intervals (2.5- and 10-min). Five metrics of resting HRV [mean interbeat interval (IBI), the standard deviation of normal IBIs (SDNN), root square mean of successive differences between IBIs (RMSSD), cardiac vagal index (CVI), and cardiac sympathetic index (CSI)] were assessed in 421 twin pairs aged 14-20 during a baseline electrocardiogram. This was done for four successive 2.5-min intervals as well as the overall 10-min interval. Heritability (h2) appeared consistent across intervals within each metric with the following estimates (collapsed across time intervals): mean IBI (h2 = 0.36-0.46), SDNN (h2 = 0.23-0.30), RMSSD (h2 = 0.36-0.39), CVI (h2 = 0.37-0.42), CSI (h2 = 0.33-0.46). Beyond additive genetic contributions, unique environment also was an important influence on HRV. Within each metric, a multivariate Cholesky decomposition further revealed evidence of genetic stability across the four successive 2.5-min intervals. The same models showed evidence for both genetic and environmental stability with some environmental attenuation and innovation. All measures of HRV were moderately heritable across time, with further analyses revealing consistent patterns of genetic and environmental influences over time. This study confirms that in an adolescent sample, the time interval used (2.5- vs. 10-min) to measure HRV time domain metrics does not affect the relative proportions of genetic and environmental influences

The genetic and environmental relationship between childhood behavioral inhibition and preadolescent anxiety

This study uses novel approaches to examine genetic and environmental influences shared between childhood behavioral inhibition (BI) and symptoms of preadolescent anxiety disorders. Three hundred and fifty-two twin pairs aged 9-13 and their mothers completed questionnaires about BI and anxiety symptoms. Biometrical twin modeling, including a direction-of-causation design, investigated genetic and environmental risk factors shared between BI and social, generalized, panic and separation anxiety. Social anxiety shared the greatest proportion of genetic (20%) and environmental (16%) variance with BI with tentative evidence for causality. Etiological factors underlying BI explained little of the risk associated with the other anxiety domains. Findings further clarify etiologic pathways between BI and anxiety disorder domains in children