Cross-Disorder Psychiatric Genomics

Cell-free DNA as a potential diagnostic biomarker in academic stress: A case-control study in young adults

Background

Stress is a pervasive issue in modern life, affecting both physical and mental health. Identifying biomarkers like cell-free DNA (cfDNA) could provide insights into stress response and help detect individuals at risk for stress-related disorders.

Objective

The aim of this study is to investigate the potential use of cfDNA as a diagnostic biomarker in individuals experiencing stress.

Methodology

A case-control analysis was conducted using convenient sampling on university participants (N = 285 cases, N = 500 controls) aged 18-24. The study assessed haematological and lipid profile parameters using the Sysmex XP-300TM automated analyzer and an automated biochemistry analyzer, and cfDNA was extracted using a standardized in house developed Phenol-Chloroform protocol and estimated using Agarose Gel Electrophoresis and Nanodrop. Statistical analysis was performed using SPSS ver. 21.0.

Results

The results indicated a significant difference between stressed individuals and healthy controls in demographic, haematological and biochemical parameters. Specifically, stressed cases had significantly higher levels of cholesterol, LDL cholesterol, triglycerides, glucose, VLDL cholesterol, and lower levels of HDL compared to healthy controls. Stressed cases also showed significantly elevated levels of circulating cfDNA relative to healthy controls.

Conclusion

These findings suggest that cfDNA may have potential as a diagnostic biomarker for stress.

The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study

BACKGROUND

Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ.

METHODS

We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association.

RESULTS

Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function.

CONCLUSIONS

We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

Evidence of genetic overlap and causal relationships between blood-based biochemical traits and human cortical anatomy

Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex. Recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in many psychiatric disorders which could be mediated by changes in the cerebral cortex. Here, we leveraged publicly available genome-wide association study data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area. Linkage disequilibrium score regression identified 191 genetically correlated biochemical-cortical trait pairings, with consistent representation of blood cell counts and other biomarkers such as C-reactive protein (CRP), haemoglobin and calcium. Spatially organised patterns of genetic correlation were additionally uncovered upon clustering of region-specific correlation profiles. Interestingly, by employing latent causal variable models, we found strong evidence suggesting CRP and vitamin D exert causal effects on region-specific cortical thickness, with univariable and multivariable Mendelian randomization further supporting a negative causal relationship between serum CRP levels and thickness of the lingual region. Our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical structure in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering

Neuropsychiatric disorders involve complex polygenic determinants as well as brain alterations. The combination of genetic inheritance and neuroimaging approaches could advance our understanding of psychiatric disorders. However, cross-disorder overlap is a current issue since psychiatric conditions share some neurogenetic correlates, symptoms, and brain effects. Exploring the impact of genetic risk on the brain across disorders could help understand commonalities across multiple psychopathologies. To do this, we first compute the linear relationship between PRS and voxel-wise grey matter volume to generate brain maps for five psychiatric and three control traits. Next, we use the biclustering approach to identify regions of the brain associated with polygenic risk scores in one or more traits. Our results demonstrate a significant overlap in brain regions connected to polygenic risk across psychiatric traits. Moreover, such brain domains are highly allied with the polygenic risk for non-psychiatric control traits. This multi-trait overlap characterizes the nonspecific relationship between neural anatomy and inherited risk factors in psychiatric conditions, and in some cases, the overlap in neural features linked to genetic risk for non-psychiatric attributes.Clinical Relevance-This study presents biclusters of multiple psychiatric and control traits. The analysis reported various brain regions, including cerebellum, cuneus, precuneus, fusiform, supplementary motor area, that show significant correlation with polygenic risk scores across diverse groups of psychiatric conditions and non-psychiatric control traits.

Genetics of anorexia nervosa: an overview of genome-wide association studies and emerging biological links

Anorexia nervosa (AN) is a complex disorder with a strong genetic component. Comorbidities are frequent and there is substantial overlap with other disorders. The lack of understanding of the molecular and neuroanatomical causes has made it difficult to develop effective treatments and it is often difficult to treat in clinical practice. Recent advances in genetics have changed our understanding of polygenic diseases, increasing the possibility of understanding better how molecular pathways are intertwined. This review synthetizes the current state of genetic research providing an overview of genome-wide association studies (GWAS) findings in AN as well as overlap with other disorders, traits, pathways, and imaging results. This paper also discusses the different putative global pathways that are contributing to the disease including the evidence for metabolic and psychiatric origin of the disease.

Psychiatry in the Digital Age: A Blessing or a Curse?

Social distancing and the shortage of healthcare professionals during the COVID-19 pandemic, the impact of population aging on the healthcare system, as well as the rapid pace of digital innovation are catalyzing the development and implementation of new technologies and digital services in psychiatry. Is this transformation a blessing or a curse for psychiatry? To answer this question, we conducted a literature review covering a broad range of new technologies and eHealth services, including telepsychiatry; computer-, internet-, and app-based cognitive behavioral therapy; virtual reality; digital applied games; a digital medicine system; omics; neuroimaging; machine learning; precision psychiatry; clinical decision support; electronic health records; physician charting; digital language translators; and online mental health resources for patients. We found that eHealth services provide effective, scalable, and cost-efficient options for the treatment of people with limited or no access to mental health care. This review highlights innovative technologies spearheading the way to more effective and safer treatments. We identified artificially intelligent tools that relieve physicians from routine tasks, allowing them to focus on collaborative doctor-patient relationships. The transformation of traditional clinics into digital ones is outlined, and the challenges associated with the successful deployment of digitalization in psychiatry are highlighted.

Psychiatric symptoms and syndromes transcending diagnostic boundaries in Indian multiplex families: The cohort of ADBS study

Syndromes of schizophrenia, bipolar disorder, obsessive-compulsive disorder, substance use disorders and Alzheimer's dementia are highly heritable. About 10-20% of subjects have another affected first degree relative (FDR), and thus represent a 'greater' genetic susceptibility. We screened 3583 families to identify 481 families with multiple affected members, assessed 1406 individuals in person, and collected information systematically about other relatives. Within the selected families, a third of all FDRs were affected with serious mental illness. Although similar diagnoses aggregated within families, 62% of the families also had members with other syndromes. Moreover, 15% of affected individuals met criteria for co-occurrence of two or more syndromes, across their lifetime. Using dimensional assessments, we detected a range of symptom clusters in both affected and unaffected individuals, and across diagnostic categories. Our findings suggest that in multiplex families, there is considerable heterogeneity of clinical syndromes, as well as sub-threshold symptoms. These families would help provide an opportunity for further research using both genetic analyses and biomarkers.

Iatrogenic opioid use disorder, chronic pain and psychiatric comorbidity: A systematic review

OBJECTIVE

A systematic review of the literature on the risks of developing iatrogenic opioid use disorders in chronic pain patients with psychiatric comorbidity.

METHODS

We conducted literature searches on Pubmed with key subjects: "chronic pain", "psychiatry", "opioids" and "opioid use disorder" and for original, English written articles published from 2000 until the first of September 2017. Final selection of the articles for review was made in a consensus between three reviewers.

RESULTS

Longitudinal studies showed a significant association between psychiatric comorbidity, especially depression and anxiety disorders and the development of problematic opioid use, more severe opioid craving and poor opioid treatment outcome (analgesia and side effects) in chronic pain patients. Cross-sectional studies showed a similar association between psychiatric disorders and problematic opioid use, where studies in specialized pain settings showed a higher prevalence of psychiatric disorders, compared to non-specialized settings.

CONCLUSIONS

This systematic review showed a significant association between psychiatric comorbidity, especially depression and anxiety disorders and the development of problematic opioid use in chronic pain patients. We therefore recommend psychiatric screening in chronic pain management. Chronic pain patients with comorbid psychiatric disorders need a multidisciplinary approach and monitoring opioid use is warranted in these patients.

Genetic Markers in Psychiatry

Psychiatric disorders such as addiction (substance use and addictive disorders), depression, eating disorders, schizophrenia, and post-traumatic stress disorder (PTSD) are severe, complex, multifactorial mental disorders that carry a high social impact, enormous public health costs, and various comorbidities as well as premature morbidity. Their neurobiological foundation is still not clear. Therefore, it is difficult to uncover new set of genes and possible genetic markers of these disorders since the understanding of the molecular imbalance leading to these disorders is not complete. The integrative approach is needed which will combine genomics and epigenomics; evaluate epigenetic influence on genes and their influence on neuropeptides, neurotransmitters, and hormones; examine gene × gene and gene × environment interplay; and identify abnormalities contributing to development of these disorders. Therefore, novel genetic approaches based on systems biology focused on improvement of the identification of the biological underpinnings might offer genetic markers of addiction, depression, eating disorders, schizophrenia, and PTSD. These markers might be used for early prediction, detection of the risk to develop these disorders, novel subtypes of the diseases and tailored, personalized approach to therapy.

GWAS of Behavioral Traits

Over the past decade, genome-wide association studies (GWAS) have evolved into a powerful tool to investigate genetic risk factors for human diseases via a hypothesis-free scan of the genome. The success of GWAS for psychiatric disorders and behavioral traits have been somewhat mixed, partly owing to the complexity and heterogeneity of these traits. Significant progress has been made in the last few years in the development and implementation of complex statistical methods and algorithms incorporating GWAS. Such advanced statistical methods applied to GWAS hits in combination with incorporation of different layers of genomics data have catapulted the search for novel genes for behavioral traits and improved our understanding of the complex polygenic architecture of these traits.This chapter will give a brief overview on GWAS and statistical methods currently used in GWAS. The chapter will focus on reviewing the current literature and highlight some of the most important GWAS on psychiatric and other behavioral traits and will conclude with a discussion on future directions.

Genetic Studies of Tic Disorders and Tourette Syndrome

Tourette syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead, TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progress in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES), and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.

Polygenic prediction of the phenome, across ancestry, in emerging adulthood

BACKGROUND

Identifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.

METHODS

This study examined a sample of emerging adults 18-22 years of age (N = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.

RESULTS

Polygenic risk for schizophrenia (SZ) in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.

CONCLUSIONS

These results demonstrate the extensive impact of genetic risk for SZ, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.

Discovery biology of neuropsychiatric syndromes (DBNS): a center for integrating clinical medicine and basic science

BACKGROUND

There is emerging evidence that there are shared genetic, environmental and developmental risk factors in psychiatry, that cut across traditional diagnostic boundaries. With this background, the Discovery biology of neuropsychiatric syndromes (DBNS) proposes to recruit patients from five different syndromes (schizophrenia, bipolar disorder, obsessive compulsive disorder, Alzheimer's dementia and substance use disorders), identify those with multiple affected relatives, and invite these families to participate in this study. The families will be assessed: 1) To compare neuro-endophenotype measures between patients, first degree relatives (FDR) and healthy controls., 2) To identify cellular phenotypes which differentiate the groups., 3) To examine the longitudinal course of neuro-endophenotype measures., 4) To identify measures which correlate with outcome, and 5) To create a unified digital database and biorepository.

METHODS

The identification of the index participants will occur at well-established specialty clinics. The selected individuals will have a strong family history (with at least another affected FDR) of mental illness. We will also recruit healthy controls without family history of such illness. All recruited individuals (N = 4500) will undergo brief clinical assessments and a blood sample will be drawn for isolation of DNA and peripheral blood mononuclear cells (PBMCs). From among this set, a subset of 1500 individuals (300 families and 300 controls) will be assessed on several additional assessments [detailed clinical assessments, endophenotype measures (neuroimaging- structural and functional, neuropsychology, psychophysics-electroencephalography, functional near infrared spectroscopy, eye movement tracking)], with the intention of conducting repeated measurements every alternate year. PBMCs from this set will be used to generate lymphoblastoid cell lines, and a subset of these would be converted to induced pluripotent stem cell lines and also undergo whole exome sequencing.

DISCUSSION

We hope to identify unique and overlapping brain endophenotypes for major psychiatric syndromes. In a proportion of subjects, we expect these neuro-endophenotypes to progress over time and to predict treatment outcome. Similarly, cellular assays could differentiate cell lines derived from such groups. The repository of biomaterials as well as digital datasets of clinical parameters, will serve as a valuable resource for the broader scientific community who wish to address research questions in the area.

Opportunities for an enhanced integration of neuroscience and genomics

Neuroimaging and genetics are two rapidly expanding fields of research. Thoughtful integration of these areas is critical for ongoing large-scale research into the genetic mechanisms underlying brain structure, function, and development. Neuroimaging genetics has been slow to evolve relative to psychiatric genetics research, and some may be unaware that new statistical methods allow for the genomic analysis of more modestly-sized imaging samples. We present a broad overview of the extant imaging genetics literature, provide an interpretation of the major problems surrounding the integration of neuroimaging and genetics, discuss the influence and impact of genetics consortia, and suggest statistical genetic analyses that expand the repertoire of imaging researchers amassing rich behavioral data in modestly-sized samples. Specific attention is paid to the creative use of polygenic risk scoring in imaging genetic analyses, with primers on the most current risk scoring applications.