Genetic and environmental contributions to the relationships between brain structure and average lifetime cigarette use

Risk of pain disorders in offspring of parents with substance use disorders

AIMS

Individuals with substance use disorders (SUD) have higher risk of developing pain disorders. This study aimed to investigate the risk of major psychiatric disorders (MPD), SUD, and pain disorders among their offspring.

METHODS

This study used data from the Taiwan National Health Research Database. The case cohort included participants who had a parent diagnosed with SUD. The matched control cohort was offspring of parents without any SUD or major psychiatric disorder (MPD). Poisson regression was applied to estimate the risk of MPD, SUD, and pain disorder between case and control cohorts.

RESULTS

We recruited 13,840 cases and 138,400 matched controls. After adjusting for demographic characteristics and family history of psychiatric disorder, the offspring of parents with SUD had higher risk for bipolar disorder (reported as risk ratio with 95% confidence interval: 2.48, 1.79-3.43), depressive disorder (2.22, 1.94-2.52), SUD (2.53, 2.18-2.92), and alcohol use disorder (1.43, 1.16-1.76) than controls. With adjustments of demographic characteristics, individual MPD, and family history of psychiatric disorder, they also presented higher risk than controls for several pain disorders, including migraine (1.43, 1.15-1.78), fibromyalgia (1.21, 1.03-1.42), dorsopathies (1.20, 1.06-1.37), dysmenorrhea (1.16, 1.04-1.29), irritable bowel syndrome (1.26, 1.11-1.43), and dyspepsia (1.14, 1.02-1.27).

CONCLUSIONS

Clinicians should be aware of the influence of parental SUD on the elevated risk for MPD, SUD, and pain disorders in their offspring.

Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents

BACKGROUND

Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood.

METHODS

Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use.

RESULTS

A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use.

CONCLUSIONS

Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life

BACKGROUND AND AIMS

Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later.

DESIGN

Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated.

SETTING

Population-based United States sample.

PARTICIPANTS/CASES

Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves.

MEASUREMENTS

Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19).

FINDINGS

In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD.

CONCLUSIONS

Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.

Gene-Environment Interactions and Stochastic Variations in the Gero-Exposome

The limited heritability of human life spans suggests an important role for gene-environment (G × E) interactions across the life span (T), from gametes to geronts. Multilevel G × E × T interactions of aging phenotypes are conceptualized in the Gero-Exposome as Exogenous and Endogenous domains. Stochastic variations in the Endogenous domain contribute to the diversity of aging phenotypes, shown for the diversity of inbred Caenorhabditis elegans life spans in the same culture environment, and for variegated gene expression of somatic cells in nematodes and mammals. These phenotypic complexities can be analyzed as 3-way interactions of gene, environment, and stochastic variations, the Tripartite Phenotype of Aging. Single-cell analyses provide tools to explore this broadening frontier of biogerontology.

The Alzheimer's Disease Exposome

INTRODUCTION

Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants.

RESULTS AND DISCUSSION

We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.

Re-investigating the effects of chronic smoking on the pathology of alcohol-related human brain damage

Both pathological and neuroimaging studies have shown that chronic alcohol abuse causes generalized white matter, but limited gray matter, volume loss. Recent neuroimaging studies suggest that tobacco smoking also causes brain atrophy in both alcoholics and neurologically normal individuals. However, a recent pathological study, employing a manual technique to determine regional volumes, found no significant effects of smoking on either global or selected regional gray matter volumes in smokers or smoking alcoholics. Here a high-resolution computerized method was employed in the same cohort to evaluate four regions where neuroimaging studies have found atrophy in smokers and alcoholics: insula, thalamus, prefrontal cortex, and anterior cingulate cortex. Brain images from 44 cases comprising 16 non-smoking controls, nine smoking controls, eight non-smoking alcoholics, and 11 smoking alcoholics were quantified. No significant differences between the groups were found, although the alcoholic groups tended to have smaller volumes in most regions. Furthermore, there were no smoking or interactive effects, and no correlation between gray matter volumes and either tobacco pack-years or lifetime alcohol consumption. These results do not support the hypotheses that tobacco smoking causes gray matter loss or that smoking potentiates gray matter atrophy in chronic alcoholics.

Brain Structure Alterations in Respect to Tobacco Consumption and Nicotine Dependence: A Comparative Voxel-Based Morphometry Study

The main purpose of this study is to examine the lifetime tobacco consumption and the degree of nicotine dependence related gray matter (GM) and white matter (WM) volume alterations in young adult-male smokers. Fifty-three long-term male smokers and 53 well-matched male healthy non-smokers participated in the study, and the smokers were respectively categorized into light and heavy tobacco consumption subgroups by pack-years and into moderate and severe nicotine dependence subgroups using the Fagerström Test for Nicotine Dependence (FTND). Voxel-based morphometry analysis was then performed, and ANCOVA analysis combined with subsequent post hoc test were used to explore the between-group brain volume abnormalities related to the smoking amount and nicotine dependence. Light and heavy smokers displayed smaller GM and WM volumes than non-smokers, while heavy smokers were found with more significant brain atrophy than light smokers in GM areas of precuneus, inferior and middle frontal gyrus, superior temporal gyrus, cerebellum anterior lobe and insula, and in WM areas of cerebellum anterior lobe. However, the contrary trend was observed regarding alterations associated with severity of nicotine dependence. Severe nicotine dependence smokers rather demonstrated less atrophy levels compared to moderate nicotine dependence smokers, especially in GM areas of precuneus, superior and middle temporal gyrus, middle occipital gyrus, posterior cingulate and insula, and in WM areas of precuneus, posterior cingulate, cerebellum anterior lobe and midbrain. The results reveal that the nicotine dependence displays a dissimilar effect on the brain volume in comparison to the cigarette consumption. Our study could provide new evidences to understand the adverse effects of smoking on the brain structure, which is helpful for further treatment of smokers.

A critical review of assays for hazardous components of air pollution

Increased mortality and diverse morbidities are globally associated with exposure to ambient air pollution (AAP), cigarette smoke (CS), and household air pollution (HAP). The AAP-CS-HAP aerosols present heterogeneous particulate matter (PM) of diverse chemical and physical characteristics. Some epidemiological models have assumed the same health hazards by PM weight for AAP, CS, and HAP regardless of the composition. While others have recognized that biological activities and toxicity will vary with components, we focus particularly on oxidation because of its major role in assay outcomes. Our review of PM assays considers misinterpretations of some chemical measures used for oxidative activity. Overall, there is low consistency across chemical and cell-based assays for oxidative and inflammatory activity. We also note gaps in understanding how much airborne PM of various sizes enter cells and organs. For CS, the body burden per cigarette may be much below current assumptions. Synergies shown for health hazards of AAP and CS suggest crosstalk in detoxification pathways mediated by AHR, NF-κB, and Nrf2. These complex genomic and biochemical interactions frustrate resolution of the toxicity of specific AAP components. We propose further strategies based on targeted gene expression based on cell-type differences.

The genetic epidemiology of substance use disorder: A review

BACKGROUND

Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention.

METHODS

The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids.

RESULTS

There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances.

CONCLUSIONS

A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.

The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design

The ABCD twin study will elucidate the genetic and environmental contributions to a wide range of mental and physical health outcomes in children, including substance use, brain and behavioral development, and their interrelationship. Comparisons within and between monozygotic and dizygotic twin pairs, further powered by multiple assessments, provide information about genetic and environmental contributions to developmental associations, and enable stronger tests of causal hypotheses, than do comparisons involving unrelated children. Thus a sub-study of 800 pairs of same-sex twins was embedded within the overall Adolescent Brain and Cognitive Development (ABCD) design. The ABCD Twin Hub comprises four leading centers for twin research in Minnesota, Colorado, Virginia, and Missouri. Each site is enrolling 200 twin pairs, as well as singletons. The twins are recruited from registries of all twin births in each State during 2006-2008. Singletons at each site are recruited following the same school-based procedures as the rest of the ABCD study. This paper describes the background and rationale for the ABCD twin study, the ascertainment of twin pairs and implementation strategy at each site, and the details of the proposed analytic strategies to quantify genetic and environmental influences and test hypotheses critical to the aims of the ABCD study.

Efficient genome-wide association in biobanks using topic modeling identifies multiple novel disease loci

Biobanks and national registries represent a powerful tool for genomic discovery, but rely on diagnostic codes that may be unreliable and fail to capture the relationship between related diagnoses. We developed an efficient means of conducting genome-wide association studies using combinations of diagnostic codes from electronic health records (EHR) for 10845 participants in a biobanking program at two large academic medical centers. Specifically, we applied latent Dirichilet allocation to fit 50 disease topics based on diagnostic codes, then conducted genome-wide common-variant association for each topic. In sensitivity analysis, these results were contrasted with those obtained from traditional single-diagnosis phenome-wide association analysis, as well as those in which only a subset of diagnostic codes are included per topic. In meta-analysis across three biobank cohorts, we identified 23 disease-associated loci with p<1e-15, including previously associated autoimmune disease loci. In all cases, observed significant associations were of greater magnitude than for single phenome-wide diagnostic codes, and incorporation of less strongly-loading diagnostic codes enhanced association. This strategy provides a more efficient means of phenome-wide association in biobanks with coded clinical data.

Effects of cigarette smoking on cortical thickness in major depressive disorder

Findings of surface-based morphometry studies in major depressive disorder (MDD) are still inconsistent. Given that cigarette smoking is highly prevalent in MDD and has documented negative effects on the brain, it is possible that some of the inconsistencies may be partly explained by cigarette use. The aim of the current study was to examine the influence of cigarette smoking on brain structure in MDD. 50 MDD patients (25 smokers and 25 non-smokers) and 22 age, education, gender and BMI matched non-smoker healthy controls underwent structural magnetic resonance imaging. Thickness and area of the cortex were measured using surface-based morphometry implemented with Freesurfer (v5.3.0). The non-smoker MDD patients had significantly increased cortical thickness, including in the left temporal cortex (p < 0.001), right insular cortex (p = 0.033) and left pre- and postcentral gyrus (p = 0.045), compared to healthy controls. We also found decreased cortical thickness in MDD patients who smoked compared to non-smoking patients in regions that overlapped with the regions found to be increased in non-smoking patients in comparison to controls. Non-smoker MDD patients had increased surface area in the right lateral occipital cortex (p = 0.009). We did not find any region where cortical thickness or surface area significantly differed between controls and either smoker MDD patients or all MDD patients. The findings of the current study suggest that cigarette smoking is associated with cortical thinning in regions found to be increased in patients with MDD. However, these results should be considered preliminary due to methodological limitations.

Development and aging of cortical thickness correspond to genetic organization patterns

There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.