Periodic Reporting for period 2 - DIVERGE (Depression in diverse populations: Unravelling the interplay between genes and environment)
Reporting period: 2022-08-01 to 2024-01-31
Depression affects a staggering 300 million people worldwide, making it a significant global health challenge. 80% of this burden falls on low- and middle-income countries.
As a complex disease, depression is caused by both genetic and environmental factors. It is crucial to explore the global factors contributing to depression so that we better understand how depression develops and can effectively design targeted interventions.
DIVERGE is a groundbreaking initiative funded by the ERC to investigate the genetic and environmental factors as well as their interplay for the first time worldwide.
The basis for this will be an extensive data resource compiled from biobanks and new studies in Pakistan and sub-Saharan Africa. By deeply analyzing genetics and characteristics of these populations, DIVERGE seeks to unravel the origins of depression and its genetic underpinnings.
Moreover, DIVERGE intends to answer a crucial question: can genetic risk factors for depression be applied universally across different populations? This is important to ensure the benefits of genomic research, such as precision medicine, are accessible to all. To address this question, new methods will be developed and implemented.
In addition to this broad exploration, the project will focus on identifying specific causes of depression. By leveraging the diversity of the collected data and employing advanced genetic models, we hope to pinpoint genetic variants associated with depression. Cutting-edge methods will be employed to uncover the biological mechanisms behind these genetic markers.
The study will also delve into the relationship between traumatic life events, especially exposure to violence, and genetic susceptibility to depression. Understanding this connection could provide insights into the varying nature of mental illness among different groups.
These innovative approaches promise to revolutionize our understanding of what causes depression, marking a significant step forward in mental health research.
As a complex disease, depression is caused by both genetic and environmental factors. It is crucial to explore the global factors contributing to depression so that we better understand how depression develops and can effectively design targeted interventions.
DIVERGE is a groundbreaking initiative funded by the ERC to investigate the genetic and environmental factors as well as their interplay for the first time worldwide.
The basis for this will be an extensive data resource compiled from biobanks and new studies in Pakistan and sub-Saharan Africa. By deeply analyzing genetics and characteristics of these populations, DIVERGE seeks to unravel the origins of depression and its genetic underpinnings.
Moreover, DIVERGE intends to answer a crucial question: can genetic risk factors for depression be applied universally across different populations? This is important to ensure the benefits of genomic research, such as precision medicine, are accessible to all. To address this question, new methods will be developed and implemented.
In addition to this broad exploration, the project will focus on identifying specific causes of depression. By leveraging the diversity of the collected data and employing advanced genetic models, we hope to pinpoint genetic variants associated with depression. Cutting-edge methods will be employed to uncover the biological mechanisms behind these genetic markers.
The study will also delve into the relationship between traumatic life events, especially exposure to violence, and genetic susceptibility to depression. Understanding this connection could provide insights into the varying nature of mental illness among different groups.
These innovative approaches promise to revolutionize our understanding of what causes depression, marking a significant step forward in mental health research.
As part of DIVERGE, we have built the first large data resource for depression genetics including data from diverse populations, utilising existing biobanks. This includes 21 cohorts with 88,316 depression cases and 902,757 controls. In terms of ancestry, the resource has the following representation: African: 36% of effective sample size, East Asian: 26%, and South Asian: 6%, Hispanic/Latin American participants: 32%.
Currently, the smallest ancestry group in AnDi are individuals of South Asian ancestry (6%). To address this, as part of DIVERGE, we established the PASCAD study, the first large study of depression genetics in Pakistan. This is an entirely new data collection to address the immense data gap. Firstly, we formed an international panel to design the study and develop a protocol which determines which questions the participants are asked (Valkovskaya, 2023, Psychiatric Genomics). When doing research with human participants, it is vital to ensure ethical research, therefore we applied and received ethical approval from all relevant review boards. We have already recruited 8,611 participants.
Using the AnDi resource, we have carried out the first genome-wide association study in ancestrally diverse samples and published the findings in the most prestigious journal in our field (Meng et al, 2024, Nature Genetics). We identified population-specific genetic loci for depression. We also carried out a multi-ancestry meta-analysis which identified 53 novel genetic loci for depression. These have significantly advanced our understanding of the disorder.
Genetic data from ancestrally diverse participants remains significantly under-used with the majority of researchers still excluding all samples from people with any non-European ancestry. A key reason is the lack of powerful, user-friendly methods. As part of this grant we are helping to address this. We have developed PAT ratios, an important addition to address a key question about our current ability to enable equitable benefits from genomic medicine.
Currently, the smallest ancestry group in AnDi are individuals of South Asian ancestry (6%). To address this, as part of DIVERGE, we established the PASCAD study, the first large study of depression genetics in Pakistan. This is an entirely new data collection to address the immense data gap. Firstly, we formed an international panel to design the study and develop a protocol which determines which questions the participants are asked (Valkovskaya, 2023, Psychiatric Genomics). When doing research with human participants, it is vital to ensure ethical research, therefore we applied and received ethical approval from all relevant review boards. We have already recruited 8,611 participants.
Using the AnDi resource, we have carried out the first genome-wide association study in ancestrally diverse samples and published the findings in the most prestigious journal in our field (Meng et al, 2024, Nature Genetics). We identified population-specific genetic loci for depression. We also carried out a multi-ancestry meta-analysis which identified 53 novel genetic loci for depression. These have significantly advanced our understanding of the disorder.
Genetic data from ancestrally diverse participants remains significantly under-used with the majority of researchers still excluding all samples from people with any non-European ancestry. A key reason is the lack of powerful, user-friendly methods. As part of this grant we are helping to address this. We have developed PAT ratios, an important addition to address a key question about our current ability to enable equitable benefits from genomic medicine.
The ERC grant enabled us to build the AnDi resource which includes 21 study cohorts from several countries and included nearly one million participants of African, East Asian, South Asian, and Hispanic/Latin American descent, including 88,316 people with major depression.
We applied state of the art methods that we and others developed to study the genetic basis of depression which significantly advanced our understanding of the mechanisms of this disease and offers exciting new paths for treatment.
Our research, published in the leading genetics journal Nature Genetics, found more than 50 new genetic loci and 205 novel genes that are associated with depression, in the first large-scale global study of the genetics of major depression in participants of diverse ancestry groups (Meng et al, 2024, Nature Genetics).
The study also showcases potential for drug repurposing, as one of the identified genes encodes a protein targeted by a common diabetes drug, while also pointing to new targets for drugs that may be developed to treat depression.
The study has made major advances identifying genes that are linked to risk of depression, both for newly-identified links and by strengthening prior evidence, and showcases some genes with potential implications for drug development, such as NDUFAF3. The protein that NDUFAF3 encodes has been implicated previously in mood instability, and it is targeted by metformin, the first-line drug for treating type 2 diabetes. Animal studies of metformin have suggested a possible link with reduced depression and anxiety, so this latest finding further suggests that additional research into metformin and depression may be warranted.
Other genes we identified may have biologically plausible links with depression, such as a gene linked to a neurotransmitter involved in goal-directed behaviour, and genes encoding a type of protein previously linked with multiple neurological conditions.
Surprisingly, we found less overlap in the genetic hits for depression across ancestry groups than expected, at about 30% (based on our new method to gauge the degree to which a genetic association found in one ancestry group is applicable to another ancestry group), which is less overlap than previously found for other traits and diseases. Therefore, it is even more important to study depression in diverse samples because some of the findings might be ancestry specific.
Cardiovascular disease is more prevalent in patients with depression. Subsequently, European ancestry studies have provided some evidence that high BMI is a causal risk factor for major depression. Ever since, it has been a matter of ongoing research to establish whether this link is due to shared metabolic mechanisms. We uncovered that the genetic correlations of depression in individuals of East Asian descent with metabolic traits were opposite to that observed for individuals of European descent, e.g. higher weight was linked to lower depression risk. The opposite direction of effect of this risk factor across populations could suggest that the link between depression and weight is social rather than metabolic in nature. This has immense implications for research into cardiovascular risk factors and depression as well as effective approaches for prevention (Giannakopoulou et al, 2021, JAMA Psychiatry).
Currently, the smallest ancestry group in AnDi are individuals of South Asian ancestry (6%). To address this, as part of DIVERGE, we established the PASCAD study, the first large study of depression genetics in Pakistan. This is an entirely new data collection and covers very detailed environmental as well as genetic information to address the immense data gap. For the next part of the programme, we will complete the collection and analyse these data to learn more about the interplay between genetic and environmental factors in causing depression.
We applied state of the art methods that we and others developed to study the genetic basis of depression which significantly advanced our understanding of the mechanisms of this disease and offers exciting new paths for treatment.
Our research, published in the leading genetics journal Nature Genetics, found more than 50 new genetic loci and 205 novel genes that are associated with depression, in the first large-scale global study of the genetics of major depression in participants of diverse ancestry groups (Meng et al, 2024, Nature Genetics).
The study also showcases potential for drug repurposing, as one of the identified genes encodes a protein targeted by a common diabetes drug, while also pointing to new targets for drugs that may be developed to treat depression.
The study has made major advances identifying genes that are linked to risk of depression, both for newly-identified links and by strengthening prior evidence, and showcases some genes with potential implications for drug development, such as NDUFAF3. The protein that NDUFAF3 encodes has been implicated previously in mood instability, and it is targeted by metformin, the first-line drug for treating type 2 diabetes. Animal studies of metformin have suggested a possible link with reduced depression and anxiety, so this latest finding further suggests that additional research into metformin and depression may be warranted.
Other genes we identified may have biologically plausible links with depression, such as a gene linked to a neurotransmitter involved in goal-directed behaviour, and genes encoding a type of protein previously linked with multiple neurological conditions.
Surprisingly, we found less overlap in the genetic hits for depression across ancestry groups than expected, at about 30% (based on our new method to gauge the degree to which a genetic association found in one ancestry group is applicable to another ancestry group), which is less overlap than previously found for other traits and diseases. Therefore, it is even more important to study depression in diverse samples because some of the findings might be ancestry specific.
Cardiovascular disease is more prevalent in patients with depression. Subsequently, European ancestry studies have provided some evidence that high BMI is a causal risk factor for major depression. Ever since, it has been a matter of ongoing research to establish whether this link is due to shared metabolic mechanisms. We uncovered that the genetic correlations of depression in individuals of East Asian descent with metabolic traits were opposite to that observed for individuals of European descent, e.g. higher weight was linked to lower depression risk. The opposite direction of effect of this risk factor across populations could suggest that the link between depression and weight is social rather than metabolic in nature. This has immense implications for research into cardiovascular risk factors and depression as well as effective approaches for prevention (Giannakopoulou et al, 2021, JAMA Psychiatry).
Currently, the smallest ancestry group in AnDi are individuals of South Asian ancestry (6%). To address this, as part of DIVERGE, we established the PASCAD study, the first large study of depression genetics in Pakistan. This is an entirely new data collection and covers very detailed environmental as well as genetic information to address the immense data gap. For the next part of the programme, we will complete the collection and analyse these data to learn more about the interplay between genetic and environmental factors in causing depression.