The impact of chronic pain and opioid use on cognitive decline and mild cognitive impairment (MCI) is unclear. We investigated these associations in early older adulthood, considering different definitions of chronic pain.

Men in the Vietnam Era Twin Study of Aging (VETSA; n = 1,042) underwent cognitive testing and medical history interviews at average ages 56, 62, and 68. Chronic pain was defined using pain intensity and interference ratings from the SF-36 over 2 or 3 waves (categorized as mild versus moderate-to-severe). Opioid use was determined by self-reported medication use. Amnestic and non-amnestic MCI were assessed using the Jak-Bondi approach. Mixed models and Cox proportional hazards models were used to assess associations of pain and opioid use with cognitive decline and risk for MCI.

Moderate-to-severe, but not mild, chronic pain intensity (β = −.10) and interference (β = −.23) were associated with greater declines in executive function. Moderate-to-severe chronic pain intensity (HR = 1.75) and interference (HR = 3.31) were associated with a higher risk of non-amnestic MCI. Opioid use was associated with a faster decline in verbal fluency (β = −.18) and a higher risk of amnestic MCI (HR = 1.99). There were no significant interactions between chronic pain and opioid use on cognitive decline or MCI risk (all p-values > .05).

Moderate-to-severe chronic pain intensity and interference related to executive function decline and greater risk of non-amnestic MCI; while opioid use related to verbal fluency decline and greater risk of amnestic MCI. Lowering chronic pain severity while reducing opioid exposure may help clinicians mitigate later cognitive decline and dementia risk.

Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.

We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).

Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.

Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.

Limited access to multiple sclerosis (MS)-focused care in rural areas can decrease the quality of life in individuals living with MS while influencing both physical and mental health.

The objectives of this research were to compare demographic and clinical outcomes in participants with MS who reside within urban, semi-urban and rural settings within Newfoundland and Labrador. All participants were assessed by an MS neurologist, and data collection included participants’ clinical history, date of diagnosis, disease-modifying therapy (DMT) use, measures of disability, fatigue, pain, heat sensitivity, depression, anxiety and disease activity.

Overall, no demographic differences were observed between rural and urban areas. Furthermore, the categorization of primary residence did not demonstrate any differences in physical disability or indicators of disease activity. A significantly higher percentage of participants were prescribed platform or high-efficacy DMTs in semi-urban areas; a higher percentage of participants in urban and rural areas were prescribed moderate-efficacy DMTs. Compared to depression, anxiety was more prevalent within the entire cohort. Comparable levels of anxiety were measured across all areas, yet individuals in rural settings experienced greater levels of depression. Individuals living with MS in either an urban or rural setting demonstrated clinical similarities, which were relatively equally managed by DMTs.

Despite greater levels of depression in rural areas, the results of this study highlight that an overall comparable level and continuity of care is provided to individuals living with MS within rural and urban Newfoundland and Labrador.

This study introduces the prostate cancer linear energy transfer sensitivity index (PCLSI) as a novel method to predict relative biological effectiveness (RBE) in prostate cancer using linear energy transfer (LET) in proton therapy based on screening for DNA repair mutations.

Five prostate cancer cell lines with DNA repair mutations known to cause sensitivity to LET and DNA repair inhibitors were examined using published data. Relative Du145 LET sensitivity data were leveraged to deduce the LET equivalent of olaparib doses. The PCLSI model was built using three of the prostate cancer cell lines (LNCaP, 22Rv1 and Du145) with DNA mutation frequency from patient cohorts. The PCLSI model was compared against two established RBE models, McNamara and McMahon, for LET-optimized prostate cancer treatment plans.

The PCLSI model relies on the presence of eight DNA repair mutations: AR, ATM, BRCA1, BRCA2, CDH1, ETV1, PTEN and TP53, which are most likely to predict increased LET sensitivity and RBE in proton therapy. In the LET-optimized plan, the PCLSI model indicates that prostate cancer cells with these DNA repair mutations are more sensitive to increased LET than the McNamara and McMahon RBE models, with expected RBE increases ranging from 11%–33% at 2keV/µm.

The PCLSI model predicts increasing RBE as a function of LET in the presence of certain genetic mutations. The integration of LET-optimized proton therapy and genetic mutation profiling could be a significant step toward the use of individualized medicine to improve outcomes using RBE escalation without the potential toxicity of physical dose escalation.

Poor weight gain in infants with single ventricle cardiac physiology between stage 1 and stage 2 palliative surgeries is associated with worse outcomes. The growth of infants with single ventricle physiology, enrolled in home monitoring programmes in the United Kingdom, has not been widely described.

To explore the growth of infants with single ventricle physiology supported by a home monitoring programme, at a tertiary centre in the South of England.

A retrospective review of two cohorts, comparing weight gain amongst infants with single ventricle physiology, before and following the implementation of a home monitoring programme. Inclusion was dependent on a diagnosis compatible with single ventricle physiology during the interstage.

Enrolment into a home monitoring programme (cohort 2) was associated with 55% more infants being discharged home during the interstage period (p < 0.05). Interstage mortality did not differ between cohorts. There were no differences in interstage growth velocity between cohorts (cohort 1 23.98 ± 11.7 g/day and cohort 2 23.82 ± 8.3 g/day); however, infants in cohort 2 experienced less growth deceleration early in life, and achieved catch-up growth at 12-23 months. Interstage nasogastric feeding, regardless of the cohort, was associated with worse growth outcomes.

A home monitoring programme for infants with single ventricle physiology provides the opportunity for infants to be safely discharged home to their families and cared for at home during the interstage. Infants in the home monitoring programme experienced better growth, achieving weight restoration at 12–23 months.

Peripheral inflammatory markers, including serum interleukin 6 (IL-6), are associated with depression, but less is known about how these markers associate with depression at different stages of the life course.

We examined the associations between serum IL-6 levels at baseline and subsequent depression symptom trajectories in two longitudinal cohorts: ALSPAC (age 10–28 years; N = 4,835) and UK Biobank (39–86 years; N = 39,613) using multilevel growth curve modeling. Models were adjusted for sex, BMI, and socioeconomic factors. Depressive symptoms were measured using the Short Moods and Feelings Questionnaire in ALSPAC (max time points = 11) and the Patient Health Questionnaire-2 in UK Biobank (max time points = 8).

Higher baseline IL-6 was associated with worse depression symptom trajectories in both cohorts (largest effect size: 0.046 [ALSPAC, age 16 years]). These associations were stronger in the younger ALSPAC cohort, where additionally higher IL-6 levels at age 9 years was associated with worse depression symptoms trajectories in females compared to males. Weaker sex differences were observed in the older cohort, UK Biobank. However, statistically significant associations (pFDR <0.05) were of smaller effect sizes, typical of large cohort studies.

These findings suggest that systemic inflammation may influence the severity and course of depressive symptoms across the life course, which is apparent regardless of age and differences in measures and number of time points between these large, population-based cohorts.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Identifying persons with HIV (PWH) at increased risk for Alzheimer’s disease (AD) is complicated because memory deficits are common in HIV-associated neurocognitive disorders (HAND) and a defining feature of amnestic mild cognitive impairment (aMCI; a precursor to AD). Recognition memory deficits may be useful in differentiating these etiologies. Therefore, neuroimaging correlates of different memory deficits (i.e., recall, recognition) and their longitudinal trajectories in PWH were examined.

We examined 92 PWH from the CHARTER Program, ages 45–68, without severe comorbid conditions, who received baseline structural MRI and baseline and longitudinal neuropsychological testing. Linear and logistic regression examined neuroanatomical correlates (i.e., cortical thickness and volumes of regions associated with HAND and/or AD) of memory performance at baseline and multilevel modeling examined neuroanatomical correlates of memory decline (average follow-up = 6.5 years).

At baseline, thinner pars opercularis cortex was associated with impaired recognition (p = 0.012; p = 0.060 after correcting for multiple comparisons). Worse delayed recall was associated with thinner pars opercularis (p = 0.001) and thinner rostral middle frontal cortex (p = 0.006) cross sectionally even after correcting for multiple comparisons. Delayed recall and recognition were not associated with medial temporal lobe (MTL), basal ganglia, or other prefrontal structures. Recognition impairment was variable over time, and there was little decline in delayed recall. Baseline MTL and prefrontal structures were not associated with delayed recall.

Episodic memory was associated with prefrontal structures, and MTL and prefrontal structures did not predict memory decline. There was relative stability in memory over time. Findings suggest that episodic memory is more related to frontal structures, rather than encroaching AD pathology, in middle-aged PWH. Additional research should clarify if recognition is useful clinically to differentiate aMCI and HAND.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.