To date, the NIH Helping to End Addiction Long-term (HEAL) Initiative has funded over 1,000 projects that aim to identify new therapeutic targets for pain and substance use disorder (SUD), develop nonpharmacological strategies for pain management, and improve overdose and addiction treatment across settings. This study conducted a portfolio analysis of HEAL’s research to assess opportunities to advance translation and implementation.

HEAL projects (FY 2018–2022) were classified into early (T0–T1) and later (T2–T4) translational stages. Eleven coders used a 54-item data collection tool based on the Consolidated Framework for Implementation Research (CFIR) to extract project characteristics (e.g., population, research setting) relevant to translation and implementation. Descriptive statistics and visualization techniques were employed to analyze and map aggregate characteristics onto CFIR’s domains (e.g., outer setting).

HEAL’s portfolio comprised 923 projects (33.7% T0–T1; 67.3% T2–T4), ranging from basic science (27.1%) and preclinical research (21.4%) to clinical (36.8%), implementation (27.1%), and dissemination research (13.1%). Most projects primarily addressed either addiction (46.3%) or pain (37.4%). Implementation-related gaps included the underrepresentation of certain populations (e.g., sexual/gender minorities: 0.5%). T0–T1 projects occurred primarily in laboratory settings (35.1%), while T2–T4 projects were concentrated in healthcare settings (e.g., hospitals: 21.6%) with limited transferability to other contexts (e.g., community: 12.9%).

Opportunities to advance translational and implementation efforts include fostering interdisciplinary collaboration, prioritizing underserved populations, engaging with community leaders and policy stakeholders, and targeting evidence-based practices in nonclinical settings. Ongoing analyses can guide strategic investments to maximize HEAL’s impact on substance use and pain crises.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).

Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.

High cognitive activity possibly reduces the risk of cognitive decline and dementia.

To investigate associations between an individual's need to engage in cognitively stimulating activities (need for cognition, NFC) and structural brain damage and cognitive functioning in the Dutch general population with and without existing cognitive impairment.

Cross-sectional data were used from the population-based cohort of the Maastricht Study. NFC was measured using the Need For Cognition Scale. Cognitive functioning was tested in three domains: verbal memory, information processing speed, and executive functioning and attention. Values 1.5 s.d. below the mean were defined as cognitive impairment. Standardised volumes of white matter hyperintensities (WMH), cerebrospinal fluid (CSF) and presence of cerebral small vessel disease (CSVD) were derived from 3T magnetic resonance imaging. Multiple linear and binary logistic regression analyses were used adjusted for demographic, somatic and lifestyle factors.

Participants (n = 4209; mean age 59.06 years, s.d. = 8.58; 50.1% women) with higher NFC scores had higher overall cognition scores (B = 0.21, 95% CI 0.17–0.26, P < 0.001) and lower odds for CSVD (OR = 0.74, 95% CI 0.60–0.91, P = 0.005) and cognitive impairment (OR = 0.60, 95% CI 0.48–0.76, P < 0.001) after adjustment for demographic, somatic and lifestyle factors. The association between NFC score and cognitive functioning was similar for individuals with and without prevalent cognitive impairment. We found no significant association between NFC and WMH or CSF volumes.

A high need to engage in cognitively stimulating activities is associated with better cognitive functioning and less presence of CSVD and cognitive impairment. This suggests that, in middle-aged individuals, motivation to engage in cognitively stimulating activities may be an opportunity to improve brain health.

Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample.

The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo’s Older Americans Normative Studies (MOANS) norms.

Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6–27% variance explained), sex (0–13%), and education (2–10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS.

Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Common mental disorders (CMDs) including depression, anxiety, and stress are very common, but it is unclear whether the last decades of social, economic, and political change have impacted incidence of CMD. This study explored temporal trends in the recorded incidence of CMD in the United Kingdom.

We used data from general practices in the United Kingdom (Clinical Practice Research Datalink) to estimate the annual recorded incidence of CMD for 2000–2020, including symptoms, diagnosis, or pharmaceutical treatment. Trends were explored by sex, age, ethnicity, region, deprivation, and comorbidity.

We included 29 480 164 individuals who were followed up for 12.5 years on average (s.d. = 6.4 years). The recorded incidence of CMD episodes was 55.9 per 1000 person-years in 2000 [95% confidence interval (CI) 55.8–56.1], increasing to 79.6 per 1000 person-years in 2019 (95% CI 79.5–79.8). Females had higher recorded incidence rates, as did those living in more deprived areas. We observed striking patterns by age over time, with rates in ages 16–24 increasing from 40.2 per 1000 in 2000 (95% CI 39.8–40.5), to 107.8 per 1000 in 2019 (95% CI 107.0–108.6). In contrast, the rates in those aged ≥55 years decreased since 2014. There were differing patterns of incidence by ethnic group, with a steeper increase in Asian, Black, and mixed groups in recent years.

Overall, the incidence of recorded CMD in the UK general practice increased between 2000 and 2019 with a small decrease in 2020. The overall trends obscured important differences across population subgroups, which may have implications for prevention.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Persons discharged from inpatient psychiatric services are at greatly elevated risk of harming themselves or inflicting violence on others, but no studies have reported gender-specific absolute risks for these two outcomes across the spectrum of psychiatric diagnoses. We aimed to estimate absolute risks for self-harm and interpersonal violence post-discharge according to gender and diagnostic category.

Danish national registry data were utilized to investigate 62,922 discharged inpatients, born 1967–2000. An age and gender matched cohort study was conducted to examine risks for self-harm and interpersonal violence at 1 year and at 10 years post-discharge. Absolute risks were estimated as cumulative incidence percentage values.

Patients diagnosed with substance misuse disorders were at especially elevated risk, with the absolute risks for either self-harm or interpersonal violence being 15.6% (95% CI 14.9, 16.3%) of males and 16.8% (15.6, 18.1%) of females at 1 year post-discharge, rising to 45.7% (44.5, 46.8%) and 39.0% (37.1, 40.8%), respectively, within 10 years. Diagnoses of personality disorders and early onset behavioral and emotional disorders were also associated with particularly high absolute risks, whilst risks linked with schizophrenia and related disorders, mood disorders, and anxiety/somatoform disorders, were considerably lower.

Patients diagnosed with substance misuse disorders, personality disorders and early onset behavioral and emotional disorders are at especially high risk for internally and externally directed violence. It is crucial, however, that these already marginalized individuals are not further stigmatized. Enhanced care at discharge and during the challenging transition back to life in the community is needed.

Schizophrenia is a heterogeneous disorder and it is unknown what causes individual variability in symptoms and cognitive ability.

To examine the association between nine clinical predictors measurable at the onset of schizophrenia and five phenotype dimensions: positive, negative (diminished expressivity), negative (motivation and pleasure), disorganised symptoms and cognitive ability.

852 participants (mean age 49 years old) with a diagnosis of schizophrenia or schizoaffective depression were included from the CardiffCOGS cross-sectional sample. Phenotype dimensions were created using confirmatory factor analysis and a 5-factor model. Associations were tested using linear regression, adjusting for age and sex. A Bonferroni correction was applied for (p<1.1x10-3) for multiple testing.

Age of onset of psychosis was significantly associated with positive symptoms (β=-0.18, p=4.0 x10-6). Lower premorbid IQ was associated with diminished expressivity (β=-0.25, p= 7.0x10-13), reduced motivation and pleasure (β=-0.23, p= 4.3x10-11), disorganised symptoms (β=-0.14, p= 7.6x10-5) and reduced cognition (β=0.54, p= 4.8x10-77). Poor premorbid social adjustment held associations with all except positive. Developmental delay was associated with reduced cognition (β=-0.35, p= 4.3x10-5). Cannabis use (year before onset), psychosocial stressors (within 6 months), childhood abuse and family history of schizophrenia held no associations.

Clinical indicators measurable at schizophrenia onset are associated with lifetime symptom variability. A younger psychosis onset is associated with more severe positive symptoms, suggesting possible age-targeted management. Pre-established links of lower premorbid IQ with poor premorbid social adjustment and negative symptom severity with cognition are strengthened. Further investigation could potentially improve diagnosis and guide treatment choice for aspects of schizophrenia with poor outcomes.

No significant relationships.

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.