JPND Biological Resource Analysis to Identify New MEchanisms and phenotypes in Neurodegenerative Diseases (BRAIN-MEND)

Neurodegenerative diseases include Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, corticobasal degeneration, multiple system atrophy and progressive supranuclear palsy. We currently classify and treat these conditions based on symptoms and clinical findings. Although this approach seems logical it does not take into account the causes of each condition or any overlap between them, which hinders the development of new treatments. A better approach would be to reclassify the different conditions based on their causes, because this would require a deep but different understanding of each condition, and new treatments could then be directly aimed at the cause. This reclassification, new understanding, and exploration of possible treatments, is the idea behind BRAIN-MEND. We will use three innovative approaches, pioneered and developed by the BRAIN-MEND consortium. We will use the latest methods in genetics and epigenetics to identify the causes of neurodegenerative diseases, and which cell systems they affect. We will use a cutting edge technique (based on a method called network analysis) to identify new drug targets from the genetic and epigenetic results. At the same time, will use machine learning to analyse medical literature and patient records to find new or under-recognized clusters of symptoms and other clinical features which might suggest new disease groups. These three different approaches: finding causes, finding drug targets, finding new disease groups, will act to complement each other so we can be sure of any new findings. A key outcome of BRAIN-MEND will be to disentangle the different neurodegenerative diseases, so that for any patient group, we understand how different causes produce the same clinical picture, while in other cases, the same cause can produce different clinical pictures. Having this new way of thinking of neurodegenerative diseases will enhance our understanding of them and make it easier to develop new treatments. Patients and caregivers will be intimately involved throughout the project, through participation in study design, and for example, development of a patient-orientated website. BRAIN-MEND partners are highly qualified to perform the work proposed, with outstanding scientific track records, direct access to the data to be studied, and expertise in the scientific methods that will be used. All the results will be publicized through medical literature, presentation at international conferences, through a consortium blog, through social media, and through the press offices of the institutions involved.

Current classification of neurodegenerative diseases (ND) is based on clinical phenotypes and does not account for underlying disease heterogeneity or overlapping disease mechanisms, hindering therapy development. Reclassification of NDs is therefore urgently needed. From a therapeutic perspective, reclassification should be based on causal and druggable factors. BRAIN-MEND will reclassify existing phenotypes using pathway and network analyses within and across complex NDs including Alzheimer Disease, Parkinson Disease, ALS, FTD, Corticobasal Degeneration, MSA, and PSP. We will use three innovative approaches, pioneered or adopted by the consortium: WP1 will apply the latest methods to identify causal genetic factors acting on molecular pathways; WP2 will apply cutting edge methods to identify epigenetic factors associated with molecular pathways of ND; and WP3 will identify drug targets from network analyses using results from WP1 and WP2 without requiring prior knowledge of mechanism. WP4 will use analysis of medical literature and patient records to identify novel or under-recognized clusters of related clinical features. These complementary approaches allow for iterative cross-validation of elucidated factors by WP1-4. BRAIN-MEND will reclassify ND phenotypes based on biologically meaningful categories corresponding to subgroups (heterogeneity) and common pathways (pleiotropy) to enhance disease understanding and facilitate drug development across the entire complex ND landscape. WP5 will manage the project and disseminate results. Patients and caregivers will be intimately involved throughout the project. Our consortium is highly qualified to perform the work proposed, as evidenced by a mean PI h-index of 61, major impact in research in neurodegeneration and neuropsychiatry, direct expertise with and access to a large and rich dataset spanning all complex NDs, track record in cross disorder analyses, and the related tools, biobanks and cell models needed.

BRAIN-MEND holds the potential to directly impact the clinic, as the overall goal is to reclassify neurodegenerations in the clinically most meaningful way, namely by shared causation and treatment profile. Table 4 summarises the main exploitable results to aid the implementation of the new classification system.

Table 4. Exploitable results and their impact

1 Ranking of known drugs for each disorder (WP3) -
Potential to help prioritise drug repositioning efforts for neurodegenerative disorders.

2 Novel small molecule identification (WP3) -
Similarly, we will rank small molecules with known protein binding profiles. These will
require more careful work-up but also represent a valuable IP and general
opportunity.

3 New neurodegenerative disease loci and genes (WP1, WP2, WP3) -
New neurodegenerative disease loci will yield new neurodegenerative disease genes
through our analyses. These potentially form high priority targets for follow-up
functional work that falls beyond the scope of this grant proposal.

4 Methods and Software (WP1, WP2, WP3) -
The funding requested does not cover method development and software. However, the
data and analysis aims are likely to spin off new questions which may need to be
addressed by new methods. We have track records in method development, hence, an
indirect outcome may be new methods and software.

5 Biomarkers (WP4) -
A list of new potential biomarkers to aid neurodegenerative disease (sub) diagnosis.

6 New classification system (WP4) -
A new classification system that groups neurodegenerative diseases according to
respectively common causative pathways, treatment profile and phenotype, which
comes with guidelines for implementation, including new potential biomarkers (see
above), as well as guidelines for consistent data collection across neurodegenerative
diseases for further research to extend and fine-tune the classification system.

Neurodegenerations and neuropsychiatric diseases impact the sexes differentially both in risk and in clinical presentation. Gender differences are therefore a fundamental part of our hypotheses, aims and work plan. BRAIN-MEND will identify sex differences and the factors mediating those sex differences. For example, our analyses in WP1 and WP2 may be informed by sex-specific eQTL, mQTL and meQTL. Socio-economic factors influencing disease will be studied through analysis of geocoding and environmental questionnaire data where available. We also give a high priority to gender balance in the research team; two of the five WP leaders are women.

The BRAIN-MEND consortium acknowledges that training of young researchers and mobility within the consortium will be beneficial for maximal knowledge transfer. Therefore, consortium partners will between them exchange at least six (PhD) students or postdoctoral researchers for 2 to 4 months during the duration of this project, and provide placement on the King's College London SGDP Summer School in Bioinformatics. The aim will be to exchange knowledge of the main research techniques between consortium members. At the project start an exchange plan will be constructed. Knowledge exchange between BRAIN-MEND and other research organizations will mainly occur through interactions with relevant external transnational initiatives.