Post-traumatic stress disorder (PTSD) is one of the most common psychiatric disorders, affecting some 8 million adults at some point in their lifetime in the United States.
Despite this, it is not clear why only some people who experience a traumatic event develop PTSD. Some researchers have suggested that the disorder is only a social construct, but previous studies have hinted that genetics plays a role.
A new study identifies a clear biological basis for PTSD.
In the largest and most diverse genetic study of PTSD to date, scientists from University of California San Diego School of Medicine and more than 130 additional institutions participating in the Psychiatric Genomics Consortium have found that PTSD has a strong genetic component similar to other psychiatric disorders.
Genetics, they write in Nature Communications, accounts for between five and 20 percent of the variability in PTSD risk following a traumatic event.
“Our long-term goal is to develop tools that might help clinicians predict who is at greatest risk for PTSD and personalize their treatment approaches,” said the study’s first and corresponding author Caroline Nievergelt, PhD, associate professor of psychiatry at UC San Diego School of Medicine and associate director of neuroscience in the Center of Excellence for Stress and Mental Health at the Veterans Affairs San Diego Healthcare System.
“We can’t always protect people from trauma. But we can treat them in the best ways possible, at the best time.”
The study team also reports that, like other psychiatric disorders and many other human traits, PTSD is highly polygenic, meaning it is associated with thousands of genetic variants throughout the genome, each making a small contribution to the disorder.
Six genomic regions called loci harbor variants that were strongly associated with disease risk, providing some clues about the biological pathways involved in PTSD.
“Based on these findings, we can say with certainty that there is just as much of a genetic component to PTSD risk as major depression and other mental illnesses,” said senior author Karestan Koenen, associate member of the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard and a professor of psychiatric epidemiology in the Harvard T.H. Chan School of Public Health.
“Our limited ability to study the living human brain and uncover the biological roots of PTSD has contributed to the lack of treatments and the stigma around this debilitating condition. Genetics helps us make new discoveries, find opportunities for new therapies, and counter that stigma.”
PTSD is polygenic
To conduct the study, Koenen, Nievergelt and colleagues collaborated with the Psychiatric Genomics Consortium’s PTSD working group and Cohen Veterans Bioscience, a non-profit organization dedicated to accelerating PTSD and traumatic brain injury research.
Together, they built a 12-country network of more than 200 researchers, assembling data and DNA samples from more than 60 groups of people with PTSD and control subjects, including the UK Biobank.
At more than 200,000 people, the combined cohort is 10 times larger than the first Psychiatric Genomics Consortium PTSD study, published in 2017, and includes both civilians and members of the military.
The cohort is also the most ancestrally diverse for any psychiatric genetics study to date, with more than 23,000 people with PTSD of European ancestry and more than 4,000 of African ancestry.
“Our study is distinguished by the fact that it’s international and is highly diverse,” Nievergelt said. “There’s greater representation here than in most studies to date.”
The team used the data to conduct a genome-wide association study (GWAS), using statistical tests to measure the effect of common genetic variants at millions of points across the genome on someone’s likelihood of developing PTSD.
The analysis uncovered DNA variants at six loci that were strongly associated with PTSD risk. Three of the six loci were specific to certain ancestral backgrounds — two European and one African — and three were only detected in men.
The six loci hint that inflammatory and immune mechanisms may be involved in the disorder, which is consistent with findings from previous studies.
Genome-wide, a substantial number of variants had some level of association with PTSD, showing the disorder to be highly polygenic.
The researchers concluded that PTSD’s heritability — the level of influence genetics has on the variability of PTSD risk in the population — is between five and 20 percent, with some variability by sex. These findings held true across different ancestral groups.
As many behavioral traits and psychiatric disorders have some shared genetic basis, the team also looked for genetic correlations between PTSD and 235 other disorders, behaviors and physical traits.
They found significant overlap with 21, including depression, schizophrenia, neuroticism, insomnia, asthma and coronary artery disease.
Genetic data from 200,000 people reveals the heritability of post-traumatic stress disorder is similar to that of depression and other forms of mental illness. The image is credited to Susanna M. Hamilton, Broad Communications.
“Similar to other mental disorders, the genetic contribution to PTSD correlates with that for many other traits,” Koenen said.
“Further research is needed to determine what this means — whether some of the same genes that influence risk for PTSD also influence risk for other diseases like, for example, depression.”
Predictive potential
In a first step toward finding ways to predict who will develop PTSD, the research team used the UK Biobank data to develop a polygenic score that could possibly predict one’s risk of developing PTSD following a traumatic event.
Polygenic scores tally the effects of millions of genetic variations into a measure that can predict an individual’s likelihood of exhibiting a certain trait or having a disorder.
The team tested their scores on data from men in the UK Biobank dataset, finding that those with the highest scores had 0.4-fold higher odds of developing than those with the lowest.
Similarly, when applied to data from the Million Veterans Program, which is studying how genes, lifestyle and military exposures affect health and illness, people with the highest scores had a significant increase in re-experiencing traumatic memories — a key PTSD symptom.
The study authors emphasized that polygenic scores are not ready for clinical use. Even larger studies with more diverse datasets are needed to improve the accuracy of PTSD prediction and confirm the genetic findings.
“If you look across psychiatric genetics, it’s taken even larger sample sizes than what we have here to make robust genetic discoveries,” Koenen said.
“This is a good start, but this needs to be a truly inclusive, large-scale, team-based scientific effort if we’re going to continue to lay the groundwork for more effective interventions and treatments for the millions of people struggling with PTSD.”
The study was led by the Psychiatric Genomics Consortium – PTSD Group and involved the efforts of more than 180 co-authors from than 130 research institutions around the world.
Disclosure: Co-author Anders Dale, PhD, is a founder of and holds equity in CorTechs Labs, Inc, and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. and receives funding through research agreements with General Electric Healthcare and Medtronic, Inc. Co-author Murray B. Stein, MD, has in the past three years been a consultant for Actelion, Aptinyx, Bionomics, Dart Neuroscience, Healthcare Management Technologies, Janssen, Neurocrine Biosciences, Oxeia Biopharmaceuticals, Pfizer, and Resilience Therapeutics. The terms of these arrangements have been reviewed and approved by UC San Diego in accordance with its conflict of interest policies.
Funding: The study was supported by the National Center for Advancing Translational Sciences, grant UL1652 TR001422, the National Blood Lung and Heart Institute grant T32 HL007909, the National Institute of Diabetes and Digestive and Kidney Diseases grant R21 DK118503 and the National Institute on Deafness and Other Communication Disorders grant R01655 DC015426, all of the National Institutes of Health.
Other Northwestern authors are first author Surabhi Bhutani, James D. Howard, Rachel Reynolds, Phyllis Zee and Jay A. Gottfried.
Post-traumatic stress disorder (PTSD) is a debilitating mental illness that can develop following a traumatic experience, such as combat, sexual assault, or natural disaster1. It occurs in ~10% of those experiencing severe trauma, with a lifetime incidence rate of 6.8−8% in the US general public2,3 and up to 15% among Operation Enduring Freedom and Operation Iraqi Freedom (OEF/OIF) veterans4,5.
The current approach to diagnosis in general clinical practice relies on clinician interviews and patient self-reports. Variation in patients’ willingness to self-disclose, as well as highly heterogeneous symptom presentations and severity levels of PTSD6, make accurate and timely diagnosis challenging.
Underdiagnoses, in particular, may result in serious, and at times fatal, outcomes that could have potentially been avoidable7–10.
The urgent need for biomarkers as an objective diagnostic and prognostic tool for PTSD cannot be overstated11,12.
Despite an international effort studying military and civilian cohorts where many molecular layers and modalities were investigated13–16, there are, as of yet, no validated blood-based PTSD biomarker panels.
Towards this end, one of the more-promising approaches, facilitated by a recent large-scale multi-site collaborative genome-wide association study (GWAS) from the Psychiatric Genomics Consortium for PTSD (PGC-PTSD)17, is genomic profiling using single-nucleotide polymorphisms (SNP’s).
PTSD genomic profiles assess the degree of genetic propensity, in probabilistic terms, for developing PTSD following a traumatic experience.
This information is of great importance not only for identifying biomarkers for disease prognosis, but also for elucidating disease etiology and mechanisms. As genetic profiles can be obtained prior to trauma exposure, they can also be used to plan preventative measures in at-risk populations, including military personnel.
For example, duty assignments, number of tours, and dwell times between tours can be adjusted in relation to risk and resilience profiles. Pre-deployment resilience building strategies and personalized early interventions can also be implemented, especially for those that are at a higher risk. Furthermore, in the long-term, enhanced understanding of the genetics of the disorder will inform the design and tailoring of effective therapeutics.
The main technical challenge in building genomic profiles, besides shortage of study samples, is the fact that the genetic architecture of PTSD, not unlike most other complex psychiatric traits18, is highly polygenic.
Individual (or even a few dozen) common SNP variants account for only a small part of the genetic influence. For instance, the largest published PTSD GWAS to date17, done with 20,000 (25% cases) participants, could not find any novel GWAS significant variant, nor could it replicate previously identified hits.
A study of this sample size had 80% power to detect a disease (causative) allele with genotype relative risk of 1.186–1.35 (assuming an additive model with disease allele frequency of 5–20% and a prevalence of 8% requiring a significance level of 5e-8). This suggests that common variants have individually small effect-sizes and are not by themselves predictive of PTSD risk.
Despite this lack of individual large effect-size common variants, small effects from many variants accumulate to result in a moderate level of heritability. Among those exposed to trauma, twin studies indicated a PTSD heritability of ~30% in men and 70% in women19,20.
Also of note, a moderate level of heritability (30%), particularly for women, was recently confirmed with SNP array-based heritability analysis17.
Hence, a sensible way of capturing the genetic liability of an individual is, instead of looking at individual genes and variants in isolation, to account for the additive effects of these small effect risk variants.
The total sum of risk variants, weighted by corresponding effect-sizes, which are usually obtained from GWAS summary statistics, is commonly known as polygenic risk score (PRS)21,22.
We investigated various issues pertaining to PTSD-PRS. First, we discussed its opportunities and limitations from a theoretical performance analysis.
Next, we constructed the PRS using GWAS summary statistics in a deeply phenotyped and well-curated cohort comprised of OIF/OEF veterans conducted by Systems Biology PTSD Biomarkers Consortium (SBPBC), hereafter referred to as the SysBio cohort. We then showed that ancestral makeup similarity between discovery and validation cohorts was a major performance determinant.
Furthermore, as a demonstration of genetic overlap among psychiatric illnesses, we use schizophrenia GWAS summary statistics to predict PTSD phenotypes. Overall, in addition to theoretical and empirical investigation of PRS prediction performance on PTSD onset and severity, we demonstrated its use in studying genetic correlation with other psychiatric disorders.
Projections from theoretical analysis
Initially, we sought to provide a preview of the roadmap ahead using analytical derivation. In light of upcoming large-scale genetic studies, this approach will also set expectations for opportunities and limitations for future genetic risk prediction studies of PTSD. These projections are predicated on standard assumptions and models from quantitative genetic theory (Supplementary Materials). Using the heritability estimate of 30% (obtained from early male twin studies and recent SNP heritability estimates for women) and an estimated disease prevalence of 8%, the optimal panel trained on an infinite number of samples would have an AUC of a little over 80% (Fig. (Fig.1).1). It should be noted that unlike most study samples, including the present study samples, where cases are intentionally oversampled so as to make up half of a study cohort (i.e., ascertainment), both the training sample (whose sample size is shown in the horizontal axis) and replication sample (whose performance is shown in the vertical axes) are assumed to be drawn randomly and independently from the general public where disease incidence rate is 8%.
Performance projections and upper bound of a genomic predictor for PTSD onset.Assuming 50,000 non-null contributing markers, coefficient of determination (fraction of variance explained) and corresponding AUC’s of genomic profiles built on finite number of samples are plotted in blue and red, respectively
Discussion
In this study, we have demonstrated that the PRS constructed from currently published GWAS results has significant, albeit insufficient for clinical use, discrimination and stratification ability for predicting PTSD diagnosis, as well as symptom severity. Theoretical analysis indicates the remaining potential of the PRS that is yet to be realized. Furthermore, the prediction ability of schizophrenia–PRS on PTSD outcomes points to the existence of polygenic overlap between PTSD and schizophrenia, confirming previously reported genetic correlation between the two disorders.
We believe that three aspects of PRS construction merit particular attention and need to be explored further in future studies. First, the method employed to construct the PRS. Conventional machine learning approaches, where the model is trained on raw genotype data, have been reported to outperform the GWAS-based approach used here37. However, such approach was not feasible because raw genotype data in large-scale studies were not available. In a GWAS-based approach, summary statistics data of GWAS are used to estimate risk score coefficients of genotype dosage. After initial use in schizophrenia21, this approach has proven successful in capturing and predicting the genetic influence on multiple complex polygenic traits38,39. Here we showed a PRS constructed in a GWAS-based approach successfully stratified patients into risk groups with distinct PTSD risk and severity levels in a cohort that is independent of the discovery GWAS samples. We expect uncertainties in the likelihoods and estimates will become lower as more data are amassed. The expected rate of this improvement is estimated from a theoretical analysis. Furthermore, advances in novel methodological approaches may accelerate this pace. Most notably, recent methods leverage information on genetically related traits to improve power of univariate association statistics40 or to improve polygenic prediction performance41,42.
Second, future polygenic risk prediction models, in addition to common single-nucleotide variants studied in this article, can incorporate rare and low frequency variants43,44 and other complex structural polymorphisms (for example, copy number variations that have been shown to be important for psychiatric disorders45). Given the rapidly evolving technological developments in whole genome and exome sequencing, this is an avenue that will become possible in the very near future. Once identified, these rare variants are likely to have larger effect-sizes (negative selection), and have potential to substantially improve prediction accuracy. Integrating other modalities, including neuroimaging biomarkers and other omics panels such as epigenomics, transcriptomics, metabolomics, and proteomics, is also promising.
Third, the PRS predicted phenotype is an important factor to consider for future studies. PTSD is characterized by a heterogeneous set of distinct symptoms. PTSD-PRS, as applied in the current study, attempts to predict genetic influences on the overall diagnosis, ignoring heterogeneity in the clinical presentation. As larger genotyped samples that are more deeply phenotyped become available, it will be possible to create genetic scores for clinical subtypes (for example, dissociative and depressive subtypes) and sub-phenotypes (for example, the four symptom clusters of PTSD) as well as specific traits, some of which might be shared with other disorders. This is particularly valuable for PTSD, and psychiatric illnesses in general, where comorbidity is prevalent and the boundaries around symptom-based diagnostic criteria are a moving target. This approach may also unearth pleiotropic patterns and help explain the widespread genetic correlations among psychiatric disorders and behavioral traits.
Ethnic diversity in genetic study cohorts (as is the case for a cohort consisting of US military members or, for that matter, the nation’s population at large) presents both unique challenges and opportunities. On one hand, beyond the mere proportional representation of the diverse US military service men and women, a genetically diverse study sample facilitates identification of trans-ethnic and population-specific causal variants46. On the other hand, genetic predictors trained on a GWAS conducted on a given ancestral group is less predictive in samples from a different ancestral group. As most genetic studies are conducted with European ancestry participants47, the prediction for non-Europeans is more difficult, particularly for African ancestry individuals, as is seen in the present study.
Going forward, it is important to keep both pros and cons of genetic biomarkers in mind. One of the reasons genetic biomarkers are attractive for psychiatric traits is the fact that samples from in vivo brain tissue, the primary disorder-relevant tissue for a psychiatric illness, is usually inaccessible. Most other “-omics” markers have tissue-specific variation, with peripheral profiles not aligning with those from the brain. Also, in addition to being a more stable marker, presently available technologies for genetic markers have a better analytical validity than other omics assays. On the other hand, information content from a single-molecular layer might be inherently limited (as shown here for genetic predictors with theoretical analyses). In order to build a robust biomarker panel, combining multiple modalities might be necessary. Addressing ethical concerns and potential misuses of genetic information also should be considered48.
Limitations of the study need to be noted. First and foremost, the current PRS has sub-optimal predictive accuracy owing in part to the fact that the discovery GWAS is still underpowered. Our target cohort is also small and comprises very well-curated samples that is not a random representative sample from the general population. Here, we almost exclusively used data from male participants. Future studies need to include larger numbers of female participants, particularly in light of the fact that women have double the rates of PTSD heritability and prevalence. Also, preliminary findings on gender-specific mechanisms of the illness have been reported49,50. In addition, functional interpretation of the PRS is also difficult owing to the large number of genetic variants it comprises.
In summary, our work contributes to the use of polygenic risk for a further understanding of PTSD risk and its underlying mechanisms, whereas also identifying areas of needed future research. Overall, these findings showed that PRS, in addition to being a powerful prognostic tool, is useful in unravelling disease etiology and mechanisms, which, in turn, will enable more personalized and novel intervention strategies. As more well-powered genetic studies become available in the near future, together with advances in whole-genome and exome sequencing, accuracy, and insight obtained from such analyses will become even more precise and useful clinically.
Source:
UCSD
Media Contacts:
Heather Buschman – UCSD
Image Source:
The image is credited to Susanna M. Hamilton, Broad Communications.
Original Research: Open access
“International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci”. Caroline Nievergelt et al.
Nature Communications doi:10.1038/s41467-019-12576-w.
