Risk assessment of substance use disorders based on the human leukocyte antigen (HLA).

Substance use disorders (SUDs) are common and costly conditions that are partially attributable to genetic factors. In light of immune system influences on neural and behavioral aspects of addiction, the present study evaluated the influence of genes involved in the human immune response, human leukocyte antigen (HLA), on SUDs. We used an immunogenetic epidemiological approach to evaluate associations between the population frequencies of 127 HLA alleles and the population prevalences of six SUDs (alcohol, amphetamine, cannabis, cocaine, opioid, and "other" dependence) in 14 countries of Continental Western Europe to identify immunogenetic profiles of each SUD and evaluate their associations. The findings revealed two primary groupings of SUDs based on their immunogenetic profiles: one group comprised cannabis and cocaine, whereas the other group comprised alcohol, amphetamines, opioids, and "other" dependence. Since each individual possesses 12 HLA alleles, the population HLA-SUD scores were subsequently used to estimate individual risk for each SUD. Overall, the findings highlight similarities and differences in immunogenetic profiles of SUDs that may influence the prevalence and co-occurrence of problematic SUDs and may contribute to assessment of SUD risk of an individual on the basis of their HLA genetic makeup.

In silico assessment of binding affinities of three dementia-protective Human Leukocyte Antigen (HLA) alleles to nine human herpes virus antigens.

BACKGROUND: Human herpes viruses (HHV) have been implicated in dementia. Class II Human Leukocyte Antigens (HLA) play a critical role in host protection from foreign antigens including herpes viruses through stimulating antibody production against them. In the present study we investigated the in silico binding affinity of 9 H HV to three Class II HLA alleles that have been found to protect against dementia: DRB1*01:01, DRB1*13:02, and DRB1*15:01. METHODS: A sliding window approach was used to partition the amino acid sequences of surface glycoproteins from HHV 1-8 into subsequences. The binding affinity of the HHV subsequences to Class II HLA surface receptor proteins was predicted using the Sturniolo method in the Immune Epitope Database and reported as a percentile rank. The binding affinity of HHV subsequences to protective alleles was compared to that of three dementia-neutral Class II HLA alleles: DRB1*03:01, DRB1*07:01, and DRB1*08:01. FINDINGS: Binding affinity varied widely for each HLA allele, HHV type, and HHV subsequence. The protective alleles had significantly higher binding affinity that than the neutral alleles. The largest differences in binding affinity between the protective and neutral alleles was shown for HHV-6A and HHV-6B, which had the best overall binding affinity with the protective alleles. INTERPRETATION: The dementia protection conferred by the three protective HLA alleles investigated here is related to their superior ability to bind and successfully eliminate HHV epitopes - in particular, HHV6 - that could otherwise cause dementia if they persisted.

Brain Function in Gulf War Illness (GWI) and Associated Mental Health Comorbidities.

GWI has affected a substantial number of Gulf War (GW) veterans. The disease involves several organ systems among which the brain is most prominent. Neurological, cognitive and mood-related (NCM) symptoms frequently dominate and are at the root of chronic ill-health and disability in veterans suffering from GWI. In addition, such symptoms frequently co-occur with diagnosable mental health disorders, predominantly posttraumatic stress disorder (PTSD). Here we investigated the possibility that increased GWI severity leads, above a threshold, to a diagnosable mental health disorder (excluding psychosis). For this purpose, we used, in separate analyses, symptom severity scores and resting-state brain functional connectivity patterns, as determined by magnetoencephalography (MEG). Two-hundred-thirty GW-era veterans participated in this study. They completed diagnostic interviews to establish the presence of GWI and assess mental health status. This distinguished 3 groups: healthy controls (N = 41), veterans with GWI and no mental illness (GWI group, N = 91), and veterans with both GWI and mental health disorder (GWI+MH, N = 98). For each veteran, symptom severity scores in the 6 GWI domains (fatigue, pain, NCM, skin, gastrointestinal, respiratory) were available as well as 9 summary measures of the distribution of Synchronous Neural Interactions (SNI) derived from the MEG recordings. We tested the hypothesis that, in the presence of GWI, the appearance of a diagnosable mental health disorder may depend on GWI symptom severity. For that purpose, we performed a logistic regression on the GWI population, where the presence (or absence) of the MH disorder was the dependent variable and the age- and gender-adjusted GWI severity in the 6-symptom domains were the predictors. The outcome was the probability that a participant will have MH disorder or not. Similarly, we tested the hypothesis that the presence of the MH disorder can be predicted by the SNI distribution patterns by performing a second logistic regression as above but with the 9 SNI measures as predictors. We found GWI symptom severity differed significantly across groups (GWI+MH > GWI > Control). SNI distributions of the GWI group also differed significantly from the other groups in a systematic hemispheric pattern, such that the presence of GWI involved predominantly the left hemisphere, and presence of mental health disorders involved, in addition, the right hemisphere. Both logistic regressions yielded highly significant outcomes, demonstrating that both GWI symptom severity and SNI distribution measures can predict the presence of MH disorder in GWI. Remarkably, the prediction probabilities for MH presence derived from the symptom-based and SNI-based logistic regressions were positively and highly statistically significantly correlated. Taken together, both objective (neural) and subjective (symptoms) indices suggest that GWI is distinct from healthy controls and varies in severity in a continuum that leads, at the higher end, to a diagnosable MH disorder. The positive correlation between the GWI symptom-based and brain-based predicted classifications provides a key link between GWI symptom severity and synchronous neural interactions in the context of mental illness.