Uncovering the genetic basis of mental illness requires data and tools that don’t rely solely on white people – this international team collects DNA samples from around the world

Mental illness is a growing public health problem. In 2019, it is estimated 1 in 8 people around the world They have been affected by mental disorders such as depression, schizophrenia, or bipolar disorder. While scientists have long known that many of these disorders run in families, their genetic basis is not entirely clear. One reason for this is that the majority of the current genetic data used in the research comes overwhelmingly from white people.

In 2003, the Human Genome Project produced the first “reference genome” of human DNA from a pool of donated samples. Residents of upstate New YorkAll of them are of European descent. Researchers in many biomedical fields still use this reference genome in their work. But it does not provide a complete picture of human genetics. A person with a different genetic origin will have a number of Differences in their DNA that was not captured by the reference sequence.

When most of the world’s ancestors are not represented in genomic data sets, studies will not be able to provide a true representation of how diseases manifested across all of humanity. Despite this, genetic diversity has not improved in genetic analyzes in the past two decades since the Human Genome Project announced its first results. As of June 2021, more than 80% Genetic studies have been conducted on people of European descent. Less than 2% included people of African descent, although these individuals have Most genetic variation for all humans.

To detect DNA driving mental illness, IAnd the Sinad Chapman and our colleagues at MIT’s Broad Institute and Harvard University are partnering with collaborators from around the world to launch Stanley Globalan initiative that seeks to collect a more diverse set of genetic samples from outside the United States and northern Europe, and train The next generation of researchers around the world. Not only does genetic data lack diversity, but it also lacks the tools and techniques that scientists use to sequence and analyze the human genome. We are therefore applying a new sequencing technology that addresses the shortcomings of previous methods that do not take into account the genetic diversity of the world’s population.

Ethical and equitable expansion of the diversity of genome data can help improve care and reduce disparities.

Global Partnerships for Global Data

To study the genes of psychiatric conditions, researchers use data from Genome-wide association studies which compares the genetic differences between people with and without a particular disease. However, these data sets are mostly On the basis of people of European originlargely because the research infrastructure and funding for large-scale genetic studies, and the scientists who conducted these studies, have historically been concentrated in Europe and the United States.

One way to bridge this gap is to sequence genetic data from diverse populations. My colleagues and I work in close partnership with geneticists, statisticians and epidemiologists in 14 countries across four continents to study the DNA of tens of thousands of mentally ill African, Asian and Latino people. We work together to recruit participants and collect DNA samples that are arranged at the Broad Institute in Massachusetts and share them with all partners for analysis.

Prioritize votes and priorities Communities and scholars are the basis of our work. All partners have common ownership of the project, including decision-making, ownership and control of samples and data. To do this, we build relationships and trust with the local communities we study and the leaders of local universities and the scholars we partner with. We work to understand local cultures and practices, and adapt our collection methods to ensure the convenience of study participants. For example, because there are different cultural sensitivities around the provision of blood and saliva samples, we adapted our practices to location to ensure the convenience of study participants.

We also share knowledge and materials freely with our partners. There is a two-way exchange of information between the Broad Institute and local teams about study progress and results, enabling continuous learning, education, and unity between teams. We strive to meet each other as we are by sharing practices and training scientists to support the development of locally grown and locally led research programmes.

The Global Initiative for Neuropsychiatric Education in Research (GINGER) program focuses on training the next generation of scientists.
Global Initiative for Teaching Neurogenetics and Psychiatry in ResearchAnd the CC BY-NC-ND

Our collaboration with African research groups provides a prime example of our model. For example, our African Research Fellows are co-leaders of grants that fund laboratory equipment, scientists, and other staff for projects based at their study sites. We help support the next generation of African geneticists and bioinformaticians through a Customized Training Program.

Variance analysis

Collecting samples from more diverse populations is only half the challenge.

Current genetic sequencing and analysis techniques do not adequately capture genetic variation across populations from around the world. That’s because these technologies are designed to detect genetic variations based on the DNA reference of people of European ancestry, who are reduce accuracy When analyzing sequences not derived from the reference genome. When these tools are applied to genetic data from other populations, they Failed to discover many rich diversity in their genomes. This could lead researchers to miss important biomedical discoveries.

To address this issue, we have developed a genome sequencing approach that can detect more genetic variation from worldwide populations. It works by concatenating files Exum Less than 2% of the genomes coding for proteins are in high detail, plus 98% of the non-protein-coding genomes are sequenced in less detail.

Different types of sequencing methods have their pros and cons.

This combined approach reduces the trade-offs that geneticists often have to make in the sequence of projects. High-deep whole genome sequencing, which reads the entire genome multiple times to obtain detailed data, is very expensive to perform on a large number of DNA samples. While Low coverage sequence It reduces costs by reading smaller parts of the genome, and may miss some important genetic differences. With our new technology, geneticists can get the best of both worlds: Exome sequencing in depth Increases the probability of accurate identification specific genes that play a role in mental illness, while Whole genome sequencing is less deep It allows researchers to manipulate large numbers of complete genomes more cost effectively.

Personalizing Medicine

We hope that this new technology will allow researchers to sequence large sample sizes from a variety of strains to capture the full range of genetic diversity. With a better understanding of the genetics of mental illness, clinicians and researchers will be better equipped to develop new treatments that work for everyone.

Genomic sequencing opened a new era of personal medicine, which promises to provide personalized treatments for each individual. This can only be done if the genetic differences of all ancestors are represented in the data sets that researchers use to make new discoveries about the disease and develop treatments.