Project description:BackgroundDrugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease.MethodsIn previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations.ResultsOur analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated.ConclusionsOur findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.
Project description:Rare diseases affect over 400 million people worldwide and less than 5% of rare diseases have an approved treatment. Fortunately, the number of underlying disease etiologies is far less than the number of diseases, because many rare diseases share a common molecular etiology. Moreover, many of these shared molecular etiologies are therapeutically actionable. Grouping rare disease patients for clinical trials based on the underlying molecular etiology, rather than the traditional, symptom-based definition of disease, has the potential to greatly increase the number of patients gaining access to clinical trials. Basket clinical trials based on a shared molecular drug target have become common in the field of oncology and have been accepted by regulatory agencies as a basis for drug approvals. Implementation of basket clinical trials in the field of rare diseases is seen by multiple stakeholders-patients, researchers, clinicians, industry, regulators, and funders-as a solution to accelerate the identification of new therapies and address patient's unmet needs.
Project description:Patients with late-onset Alzheimer's disease (LOAD) frequently manifest comorbid neuropsychiatric symptoms with depression and anxiety being most frequent, and individuals with major depressive disorder (MDD) have an increased prevalence of LOAD. This suggests shared etiologies and intersecting pathways between LOAD and MDD. We performed pleiotropy analyses using LOAD and MDD GWAS data sets from the International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium (PGC), respectively. We found a moderate enrichment for SNPs associated with LOAD across increasingly stringent levels of significance with the MDD GWAS association (LOAD|MDD), of maximum four and eightfolds, including and excluding the APOE-region, respectively. Association analysis excluding the APOE-region identified numerous SNPs corresponding to 40 genes, 9 of which are known LOAD-risk loci primarily in chromosome 11 regions that contain the SPI1 gene and MS4A genes cluster, and others were novel pleiotropic risk-loci for LOAD conditional with MDD. The most significant associated SNPs on chromosome 11 overlapped with eQTLs found in whole-blood and monocytes, suggesting functional roles in gene regulation. The reverse conditional association analysis (MDD|LOAD) showed a moderate level, ~sevenfold, of polygenic overlap, however, no SNP showed significant association. Pathway analyses replicated previously reported LOAD biological pathways related to immune response and regulation of endocytosis. In conclusion, we provide insights into the overlapping genetic signatures underpinning the common phenotypic manifestations and inter-relationship between LOAD and MDD. This knowledge is crucial to the development of actionable targets for novel therapies to treat depression preceding dementia, in an effort to delay or ultimately prevent the onset of LOAD.
Project description:Epidemiological evidence supports the observation that subjects with type 2 diabetes (T2D) are at higher risk to develop Alzheimer's disease (AD). However, whether and how these two conditions are causally linked is unknown. Possible mechanisms include shared genetic risk factors, which were investigated in this study based on recent genome wide association study (GWAS) findings. In order to achieve our goal, we retrieved single nucleotide polymorphisms (SNPs) associated with T2D and AD from large-scale GWAS meta-analysis consortia and tested for overlap among the T2D- and AD-associated SNPs at various p-value thresholds. We then explored the function of the shared T2D/AD GWAS SNPs by leveraging expressional quantitative trait loci, pathways, gene ontology data, and co-expression networks. We found 927 SNPs associated with both AD and T2D with p-value ≤0.01, an overlap significantly larger than random chance (overlapping p-value of 6.93E-28). Among these, 395 of the shared GWAS SNPs have the same risk allele for AD and T2D, suggesting common pathogenic mechanisms underlying the development of both AD and T2D. Genes influenced by shared T2D/AD SNPs with the same risk allele were first identified using a SNP annotation variation (ANNOVAR) software, followed by using Association Protein-Protein Link Evaluator (DAPPLE) software to identify additional proteins that are known to physically interact with the ANNOVAR gene annotations. We found that gene annotations from ANNOVAR and DAPPLE significantly enriched specific KEGG pathways pertaining to immune responses, cell signaling and neuronal plasticity, cellular processes in which abnormalities are known to contribute to both T2D and AD pathogenesis. Thus, our observation suggests that among T2D subjects with common genetic predispositions (e.g., SNPs with consistent risk alleles for T2D and AD), dysregulation of these pathogenic pathways could contribute to the elevated risks for AD in subjects. Interestingly, we found that 532 of the shared T2D/AD GWAS SNPs had divergent risk alleles in the two diseases. For individual shared T2D/AD SNPs with divergent alleles, one of the allelic forms may contribute to one of the diseases (e.g., T2D), but not necessarily to the other (e.g., AD), or vice versa. Collectively, our GWAS studies tentatively support the epidemiological observation of disease concordance between T2D and AD. Moreover, the studies provide the much needed information for the design of future novel therapeutic approaches, for a subpopulation of T2D subjects with genetic disposition to AD, that could benefit T2D and reduce the risk for subsequent development of AD.
Project description:We wished to determine whether rare diseases patients from India had been enrolled in international trials to develop novel orphan drugs. There are two reasons to be interested in this. (a) Different ethnic or racial groups may respond differently to a particular drug. India has huge ethnic diversity, and to exclude such participants is to severely limit the diversity of any trial; (b) Even if a suitable drug for a rare disease is available in India, it may be astronomically priced, in a country where most healthcare expenditure is out-of-pocket. We identified 63 orphan drugs, approved by the US Food and Drug Administration (FDA) after 2008, for which there were 202 trials in the US government's clinical trial registry, ClinicalTrials.gov. Only nine of these trials had run in India. These trials pertained to six drugs. The drugs were for the conditions B-cell Lymphoma, Chronic Myeloid Leukemia, Gaucher disease Type 1, Malaria, Myeloma and Pulmonary Arterial Hypertension. Further research is required as to why patients from India are not part of foreign drug development programmes for rare diseases. We then asked how many of the remaining 193 trials had recruited people of Indian origin, residing in other countries, and found that not more than 1% of these trials had done so. Also, only 11 of the 193 trials had recruited from other lower income countries. Participation from low-income countries in trials for orphan drugs is poor.
Project description:Several microRNAs which assosiate with Hirschsprung's disease were screened from 271 differentially expressed microRNAs between pathological changed colon segments of Hirschsprung's Disease and normal colon.These identified miRNAs could be used as diagnostic markers of HSCR segments.
Project description:Jacob disease is a rare entity consisting of the formation of a pseudojoint between the inner surface of the zygoma and the coronoid process. This requires constant contact between the two implicated surfaces. It can be achieved by two mechanisms: one by an enlarged coronoid process and two by an anterior displacement of the coronoid process caused by a temporomandibular joint (TMJ) disorder. Although von Langenbeck described coronoid process hyperplasia in 1853, Oscar Jacob was the first author to describe the pathology in 1899. Since then, only a few cases have been published in the literature. The authors report a rare case of Jacob disease caused by an osteochondroma of the coronoid process, which is even less common, and review the literature.
Project description:IntroductionLate-onset Alzheimer's disease (LOAD) manifests comorbid neuropsychiatric symptoms and posttraumatic stress disorder (PTSD) is associated with an increased risk for dementia in late life, suggesting the two disorders may share genetic etiologies.MethodsWe performed genetic pleiotropy analysis using LOAD and PTSD genome-wide association study (GWAS) datasets from white and African-American populations, followed by functional-genomic analyses.ResultsWe found an enrichment for LOAD across increasingly stringent levels of significance with the PTSD GWAS association (LOAD|PTSD) in the discovery and replication cohorts and a modest enrichment for the reverse conditional association (PTSD|LOAD). LOAD|PTSD association analysis identified and replicated the MS4A genes region. These genes showed similar expression pattern in brain regions affected in LOAD, and across-brain-tissue analysis identified a significant association for MS4A6A. The African-American samples showed moderate enrichment; however, no false discovery rate-significant associations.DiscussionWe demonstrated common genetic signatures for LOAD and PTSD and suggested immune response as a common pathway for these diseases.
Project description:The comorbidity of Alzheimer's disease (AD) and age-related macular degeneration (AMD) has been established in clinical and genetic studies. There is growing interest in determining the shared environmental factors associated with both conditions. Recent advancements in record linkage techniques enable us to identify the contributing factors to AD and AMD from a wide range of variables. As such, we first constructed a knowledge graph based on the literature, which included all statistically significant risk factors for AD and AMD. An environment-wide association study (EWAS) was conducted to assess the contribution of various environmental factors to the comorbidity of AD and AMD based on the UK biobank. Based on the conditional Q-Q plots and Bayesian algorithm, several shared environmental factors were identified, which could be categorized into the domains of health condition, biological sample parameters, body index, and attendance availability. Finally, we generated a shared etiology landscape for AD and AMD by combining existing knowledge with our novel findings.