Genetics of Parkinson disease and essential tremor

Brain structure comparison among Parkinson disease, essential tremor, and healthy controls using 7T MRI

Both Parkinson disease (PD) and Essential tremor (ET) are movement disorders causing tremors in elderly individuals. Although PD and ET are different disease, they often present with similar initial symptoms, making their differentiation challenging with magnetic resonance imaging (MRI) techniques. This study aimed to identify structural brain differences among PD, ET, and health controls (HCs) using 7-Tesla (T) MRI. We assessed the whole-brain parcellation in gray matter volume, thickness, subcortical volume, and small regions of basal ganglia in PD (n = 18), ET (n = 15), and HCs (n = 18), who were matched for age and sex. Brain structure analysis was performed automatic segmentation through Freesurfer software. Small regions of basal ganglia were manually segmented by ITK-SNAP. Additionally, we examined the associations between clinical indicators (symptom duration, unified Parkinson diseases rating scale (UPDRS), and clinical rating scale for tremor (CRST)) and brain structure. PD showed a significant reduction in gray matter volume in the postcentral region compared to ET. ET showed a significant reduction in cerebellum volume compared to HCs. There was a negative correlation between CRST scores (B and C) and gray matter thickness in right superior frontal in ET. This study demonstrated potential of 7T MRI in differentiating brain structure differences among PD, ET, and HCs. Specific findings, such as parietal lobe atrophy in PD compared to ET and cerebellum atrophy in ET compared to HCs, the importance of advanced imaging techniques in accurately diagnosing and distinguishing between movement disorders that present with similar initial symptoms.

A sporadic Parkinson's disease model via silencing of the ubiquitin-proteasome/E3 ligase component, SKP1A

Our and other's laboratory microarray-derived transcriptomic studies in human PD substantia nigra pars compacta (SNpc) samples have opened an avenue to concentrate on potential gene intersections or cross-talks along the dopaminergic (DAergic) neurodegenerative cascade in sporadic PD (SPD). One emerging gene candidate identified was SKP1A (p19, S-phase kinase-associated protein 1A), found significantly decreased in the SNpc as confirmed later at the protein level. SKP1 is part of the Skp1, Cullin 1, F-box protein (SCF) complex, the largest known class of sophisticated ubiquitin-proteasome/E3-ligases and was found to directly interact with FBXO7, a gene defective in PARK15-linked PD. This finding has led us to the hypothesis that a targeted site-specific reduction of Skp1 levels in DAergic neuronal cell culture and animal systems may result in a progressive loss of DAergic neurons and hopefully recreate motor disabilities in animals. The second premise considers the possibility that both intrinsic and extrinsic factors (e.g., manipulation of selected genes and mitochondria impairing toxins), alleged to play central roles in DAergic neurodegeneration in PD, may act in concert as modifiers of Skp1 deficiency-induced phenotype alterations ('dual-hit' hypothesis of neurodegeneration). To examine a possible role of Skp1 in DAergic phenotype, we have initially knocked down the expression of SKP1A gene in an embryonic mouse SN-derived cell line (SN4741) with short hairpin RNA (shRNA) lentiviruses (LVs). The deficiency of SKP1A closely recapitulated cardinal features of the DAergic pathology of human PD, such as decreased expression of DAergic phenotypic markers and cell cycle aberrations. Furthermore, the knocked down cells displayed a lethal phenotype when induced to differentiate exhibiting proteinaceous round inclusion structures, which were almost identical in composition to human Lewy bodies, a hallmark of PD. These findings support a role for Skp1 in neuronal phenotype, survival, and differentiation. The identification of Skp1 as a key player in DAergic neuron function suggested that a targeted site-specific reduction of Skp1 levels in mice SNpc may result in a progressive loss of DAergic neurons and terminal projections in the striatum. The injected LV SKP1shRNA to mouse SN resulted in decreased expression of Skp1 protein levels within DAergic neurons and loss of tyrosine hydroxylase immunoreactivity (TH-IR) in both SNpc and striatum that was accompanied by time-dependent motor disabilities. The reduction of the vertical movements, that is rearing, may be reminiscent of the early occurrence of hypokinesia and axial, postural instability in PD. According to the 'dual-hit' hypothesis of neurodegenerative diseases, it is predicted that gene-gene and/or gene-environmental factors would act in concert or sequentially to propagate the pathological process of PD. Our findings are compatible with this conjecture showing that the genetic vulnerability caused by knock down of SKP1A renders DAergic SN4741 cells especially sensitive to genetic reduction of Aldh1 and exposure to the external stressors MPP+ and DA, which have been implicated in PD pathology. Future consideration should be given in manipulation SKP1A expression as therapeutic window, via its induction genetically or pharmacological, to prevent degeneration of the nigra striatal dopamine neurons, since UPS is defective.

MicroRNA339 Targeting PDXK Improves Motor Dysfunction and Promotes Neurite Growth in the Remote Cortex Subjected to Spinal Cord Transection

Spinal cord injury (SCI) is a fatal disease that can cause severe disability. Cortical reorganization subserved the recovery of spontaneous function after SCI, although the potential molecular mechanism in this remote control is largely unknown. Therefore, using proteomics analysis, RNA interference/overexpression, and CRISPR/Cas9 in vivo and in vitro, we analyzed how the molecular network functions in neurological improvement, especially in the recovery of motor function after spinal cord transection (SCT) via the remote regulation of cerebral cortex. We discovered that the overexpression of pyridoxal kinase (PDXK) in the motor cortex enhanced neuronal growth and survival and improved locomotor function in the hindlimb. In addition, PDXK was confirmed as a target of miR-339 but not miR-124. MiR-339 knockout (KO) significantly increased the neurite outgrowth and decreased cell apoptosis in cortical neurons. Moreover, miR-339 KO rats exhibited functional recovery indicated by improved Basso, Beattie, and Bresnehan (BBB) score. Furthermore, bioinformatics prediction showed that PDXK was associated with GAP43, a crucial molecule related to neurite growth and functional improvement. The current research therefore confirmed that miR-339 targeting PDXK facilitated neurological recovery in the motor cortex of SCT rats, and the underlying mechanism was associated with regulating GAP43 in the remote cortex of rats subjected to SCT. These findings may uncover a new understanding of remoting cortex control following SCI and provide a new therapeutic strategy for the recovery of SCI in future clinical trials.

Assessment of three essential tremor genetic loci in sporadic Parkinson's disease in Eastern China

Objective

The aim of this study was to investigate potential genetic overlap between essential tremor and Parkinson's disease in a cohort of 825 subjects from an Eastern Chinese population.

Methods

A total of 441 Parkinson's disease patients and 384 healthy controls were recruited. The MassARRAY System was used to detect three essential tremor‐related single nucleotide polymorphisms. Odds ratio (OR) and 95% confidential interval (CI) were calculated to assess the relationship between polymorphisms and Parkinson's disease susceptibility.

Results

Our results demonstrated that the odds ratios of rs3794087 of SLC1A2, rs9652490 of LINGO1, and rs17590046 of PPARGC1A were 0.71 (95% CI = 0.55‐0.91), 0.99 (95% CI = 0.78‐1.26), and 0.88 (95% CI = 0.62‐1.25), respectively.

Conclusion

An essential tremor SNP (rs3794087 of SLC1A2) is associated with a decreased risk of PD in the Eastern Han Chinese population, while rs9652490 (LINGO1) and rs17590046 (PPARGC1A) do not show an association.

Central Nervous System-Derived Exosomal Alpha-Synuclein in Serum May Be a Biomarker in Parkinson's Disease

Parkinson's disease (PD) is a common movement disorder. Alpha-synuclein (α-synuclein) plays a critical role in PD. In this study, we evaluated the level of central nervous system (CNS)-derived exosomal α-synuclein in serum, which may be regarded as a specific peripheral biomarker for PD. We recruited patients with PD in the early stage along with essential tremor (ET), and we recruited age- and gender-matched healthy subjects as healthy controls (HC). We divided patients with PD into the tremor-dominant (TD) group and the non-tremor-dominant (NTD) group. We evaluated the levels of α-synuclein in CNS-derived exosomes in serum samples. As a result, there was a significant difference between four groups (p<0.05). This level was lower in the PD group than in the ET and HC groups (p<0.05). Among the PD group, this level was lower in the NTD group than in the TD group (p<0.05). Furthermore, the performance of serum CNS-derived exosomal α-synuclein was found to moderately aid in PD diagnosis (AUC=0.675, p<0.05) and had a potential to diagnose NTD (AUC=0.761, p<0.05). Therefore, CNS-derived exosomal α-synuclein in the serum may be regarded as a biomarker to identify PD from ET and HC in the early stage. It may also be used to identify different motor types in PD. The pathogenesis of PD in different motor types may be different, which needs further research.

Genetic Analysis of LRRK1 and LRRK2 Variants in Essential Tremor Patients

AIMS

Essential tremor (ET) is one of the most common adult-onset movement disorders. ET and Parkinson's disease (PD) overlap clinically and pathologically, which prompted this investigation into the association of PD risk variants in ET patients. This study was designed to explore the role of variants of two PD-related genes LRRK1 and LRRK2 in a Han Chinese ET population.

MATERIALS AND METHODS

Genetic analysis of LRRK1, rs2924835, and LRRK2, rs34594498, rs34410987, and rs33949390 variants was conducted on 200 Han Chinese patients with ET and 434 ethnically matched normal controls.

RESULTS

No statistically significant differences were identified in either genotypic or allelic frequencies of variants between the ET patients and the control cohort (all p > 0.05). Haplotype analysis of three LRRK2 variants (rs34594498, rs34410987, and rs33949390) showed no haplotypes displayed an association with ET risk (all p > 0.05).

CONCLUSIONS

The data suggest that LRRK1 variant (rs2924835) and LRRK2 variants (rs34594498, rs34410987, and rs33949390) are not associated with ET in this Han Chinese population.

Mutation Analysis of HTRA2 Gene in Chinese Familial Essential Tremor and Familial Parkinson's Disease

Background. HTRA2 has already been nominated as PARK13 which may cause Parkinson's disease, though there are still discrepancies among these results. Recently, Gulsuner et al.'s study found that HTRA2 p.G399S is responsible for hereditary essential tremor and homozygotes of this allele develop Parkinson's disease by examining a six-generation family segregating essential tremor and essential tremor coexisting with Parkinson's disease. We performed this study to validate the condition of HTRA2 gene in Chinese familial essential tremor and familial Parkinson's disease patients, especially essential tremor. Methods. We directly sequenced all eight exons, exon-intron boundaries, and part of the introns in 101 familial essential tremor patients, 105 familial Parkinson's disease patients, and 100 healthy controls. Results. No exonic variant was identified, while one exon-intron boundary variant (rs2241028) and one intron variant (rs2241027) were detected, both with no clinical significance and uncertain function. There was no difference in allele, genotype, and haplotype between groups. Conclusions. HTRA2 exonic variant might be rare among Chinese Parkinson's disease and essential tremor patients with family history, and HTRA2 may not be the cause of familial Parkinson's disease and essential tremor in China.

Heterozygous PINK1 p.G411S increases risk of Parkinson's disease via a dominant-negative mechanism

See Gandhi and Plun-Favreau (doi:10.1093/aww320) for a scientific commentary on this article.

Heterozygous mutations in recessive Parkinson’s disease genes have been postulated to increase disease risk. Puschmann et al. report a genetic association between heterozygous PINK1 p.G411S and Parkinson’s disease. They provide structural and functional explanations for a partial dominant-negative effect of the mutant protein, which impairs wild-type PINK1 activity through hetero-dimerization.

See Gandhi and Plun-Favreau (doi:10.1093/aww320) for a scientific commentary on this article.

It has been postulated that heterozygous mutations in recessive Parkinson’s genes may increase the risk of developing the disease. In particular, the PTEN-induced putative kinase 1 (PINK1) p.G411S (c.1231G>A, rs45478900) mutation has been reported in families with dominant inheritance patterns of Parkinson’s disease, suggesting that it might confer a sizeable disease risk when present on only one allele. We examined families with PINK1 p.G411S and conducted a genetic association study with 2560 patients with Parkinson’s disease and 2145 control subjects. Heterozygous PINK1 p.G411S mutations markedly increased Parkinson’s disease risk (odds ratio = 2.92, P = 0.032); significance remained when supplementing with results from previous studies on 4437 additional subjects (odds ratio = 2.89, P = 0.027). We analysed primary human skin fibroblasts and induced neurons from heterozygous PINK1 p.G411S carriers compared to PINK1 p.Q456X heterozygotes and PINK1 wild-type controls under endogenous conditions. While cells from PINK1 p.Q456X heterozygotes showed reduced levels of PINK1 protein and decreased initial kinase activity upon mitochondrial damage, stress-response was largely unaffected over time, as expected for a recessive loss-of-function mutation. By contrast, PINK1 p.G411S heterozygotes showed no decrease of PINK1 protein levels but a sustained, significant reduction in kinase activity. Molecular modelling and dynamics simulations as well as multiple functional assays revealed that the p.G411S mutation interferes with ubiquitin phosphorylation by wild-type PINK1 in a heterodimeric complex. This impairs the protective functions of the PINK1/parkin-mediated mitochondrial quality control. Based on genetic and clinical evaluation as well as functional and structural characterization, we established p.G411S as a rare genetic risk factor with a relatively large effect size conferred by a partial dominant-negative function phenotype.

Derivation, Characterization, and Neural Differentiation of Integration-Free Induced Pluripotent Stem Cell Lines from Parkinson's Disease Patients Carrying SNCA, LRRK2, PARK2, and GBA Mutations

We report generation of induced pluripotent stem cell (iPSC) lines from ten Parkinson’s disease (PD) patients carrying SNCA, PARK2, LRRK2, and GBA mutations, and one age-matched control. After validation of pluripotency, long-term genome stability, and integration-free reprogramming, eight of these lines (one of each SNCA, LRRK2 and GBA, four PARK2 lines, and the control) were differentiated into neural stem cells (NSC) and subsequently to dopaminergic cultures. We did not observe significant differences in the timeline of neural induction and NSC derivation between the patient and control line, nor amongst the patient lines, although we report considerable variability in the efficiency of dopaminergic differentiation among patient lines. We performed whole genome expression analyses of the lines at each stage of differentiation (fibroblast, iPSC, NSC, and dopaminergic culture) in an attempt to identify alterations by large-scale evaluation. While gene expression profiling clearly distinguished cells at different stages of differentiation, no mutation-specific clustering or difference was observed, though consistent changes in patient lines were detected in genes associated mitochondrial biology. We further examined gene expression in a stress model (MPTP-induced dopaminergic neuronal death) using two clones from the SNCA triplication line, and detected changes in genes associated with mitophagy. Our data suggested that even a well-characterized line of a monogenic disease may not be sufficient to determine the cause or mechanism of the disease, and highlights the need to use more focused strategies for large-scale data analysis.

Models of α-synuclein aggregation in Parkinson's disease

Parkinson's disease (PD) is not only characterized by motor disturbances but also, by cognitive, sensory, psychiatric and autonomic dysfunction. It has been proposed that some of these symptoms might be related to the widespread pathology of α-synuclein (α-syn) aggregation in different nuclei of the central and peripheral nervous system. However, the pathogenic formation of α-syn aggregates in different brain areas of PD patients is poorly understood. Most experimental models of PD are valuable to assess specific aspects of its pathogenesis, such as toxin-induced dopaminergic neurodegeneration. However, new models are required that reflect the widespread and progressive formation of α-syn aggregates in different brain areas. Such α-syn aggregation is induced in only a few animal models, for example perikaryon inclusions are found in rats administered rotenone, aggregates with a neuritic morphology develop in mice overexpressing either mutated or wild-type α-syn, and in Smad3 deficient mice, aggregates form extensively in the perikaryon and neurites of specific brain nuclei. In this review we focus on α-syn aggregation in the human disorder, its genetics and the availability of experimental models. Indeed, evidences show that dopamine (DA) metabolism may be related to α-syn and its conformational plasticity, suggesting an interesting link between the two pathological hallmarks of PD: dopaminergic neurodegeneration and Lewy body (LB) formation.

Evaluating Familial Essential Tremor with Novel Genetic Approaches: Is it a Genotyping or Phenotyping Issue?

Background

Essential tremor is a common movement disorder with a strong heritable component. Large families with inherited forms of essential tremor have undergone genetic analyses by different approaches. However, our knowledge of genetic variants unequivocally linked to essential tremor is remarkably limited. Several explanations have been put forth to explain this challenge, including the possibility of mutations in non-coding areas of the genome.

Methods

We encountered a family with highly penetrant, autosomal dominant tremor. We hypothesized that, if a single coding gene mutation was responsible for the phenotype, novel genetic tools would allow us to identify it. We employed single nucleotide polymorphism (SNP) arrays in 17 members of this family followed by next generation whole-exome sequencing in five affected subjects.

Results

We did not identify any copy number variant or mutation that segregated with the disease phenotype.

Discussion

This study emphasizes the remarkably challenging field of tremor genetics and indicates that future studies should perhaps shift to analysis of the non-coding genome.

Behavioral testing regimens in genetic-based animal models of Parkinson's disease: cogencies and caveats

Although the onset and progression of Parkinson's disease (PD) is fundamentally sporadic, identification of several of the genes implicated in the disease has provided significant insight concerning patho-physiological mechanisms potentially underlying sporadic PD. Moreover, such studies have caused a revolution in the way researchers view the disease. Since single genes responsible for rare familial forms of the disease have only been identified within the past few years, animal models based on these defects have only recently been generated, thereby not leaving a lot of time for their evaluation and subsequent improvement. The current article provides an extensive review of the major motor and non-motor behavioral tests used in genetically-induced Parkinsonian animals. Moreover, we assess the insights concerning the etiopathogenesis of PD generated from use of such tests and how these have improved available treatment strategies for alleviating aspects of sporadic and non-sporadic parkinsonism.

Key issues in essential tremor genetics research: Where are we now and how can we move forward?

Background

Genetics research is an avenue towards understanding essential tremor (ET). Advances have been made in genetic linkage and association: there are three reported ET susceptibility loci, and mixed but growing data on risk associations. However, causal mutations have not been forthcoming. This disappointing lack of progress has opened productive discussions on challenges in ET and specifically ET genetics research, including fundamental assumptions in the field.

Methods

This article reviews the ET genetics literature, results to date, the open questions in ET genetics and the current challenges in addressing them.

Results

Several inherent ET features complicate genetic linkage and association studies: high potential phenocopy rates, inaccurate tremor self-reporting, and ET misdiagnoses are examples. Increasing use of direct examination data for subjects, family members, and controls is one current response. Smaller moves towards expanding ET phenotype research concepts into non-tremor features, clinically disputed ET subsets, and testing phenotype features instead of clinical diagnosis against genetic data are gradually occurring. The field has already moved to considering complex trait mechanisms requiring detection of combinations of rare genetic variants. Hypotheses may move further to consider novel mechanisms of inheritance, such as epigenetics.

Discussion

It is an exciting time in ET genetics as investigators start moving past assumptions underlying both phenotype and genetics experimental contributions, overcoming challenges to collaboration, and engaging the ET community. Multicenter collaborative efforts comprising rich longitudinal prospective phenotype data and neuropathologic analysis combined with the latest in genetics experimental design and technology will be the next wave in the field.

Interactogeneous: disease gene prioritization using heterogeneous networks and full topology scores

Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease.

Update on genetics of parkinsonism

BACKGROUND

Major progress in genetic studies of Parkinson's disease (PD) and parkinsonism has been achieved in the last two decades.

OBJECTIVE

We provide a brief review of the current status of PARK and non-PARK loci/genes, and discuss two new genes: eIF4G1 and VPS35.

METHODS

The literature on PARK and non-PARK loci/genes was reviewed and some novel information on two new genes is provided.

RESULTS

There are 18 PARK loci. The symptomatic carriers of these genes usually present with parkinsonism, although additional clinical features can be seen during the course of the disease. Carriers of non-PARK loci/genes frequently present with a mixed phenotype that includes parkinsonism and additional clinical features. Carriers of the eIF4G1 and VPS35 genes present with a parkinsonian phenotype. The pathology of eIF4G1 is of the α-synuclein type; the pathology of VPS35 is unknown.

CONCLUSION

The current genetic classification of PD/parkinsonism genes is not ideal. The pathological classification based on the accumulation of particular proteins/inclusions is also misleading since there are kindred with a single mutation but pleomorphic pathology. A better classification of neurodegenerative conditions is needed. It is hoped that the genetic studies will lead to better therapies.

Positional integratomic approach in identification of genomic candidate regions for Parkinson's disease

MOTIVATION

Recent abundance of data from studies employing high-throughput technologies to reveal alterations in human disease on genomic, transcriptomic, proteomic and other levels, offer the possibility to integrate this information into a comprehensive picture of molecular events occurring in human disease. Diversity of data originating from these studies presents a methodological obstacle in the integration process, also due to difficulties in choosing the optimal unified denominator that would allow inclusion of variables from various types of studies. We present a novel approach for integration of such multi-origin data based on positions of genetic alterations occurring in human diseases. Parkinson's disease (PD) was chosen as a model for evaluation of our methodology.

METHODS

Datasets from various types of studies in PD (linkage, genome-wide association, transcriptomic and proteomic studies) were obtained from online repositories or were extracted from available research papers. Subsequently, human genome assembly was subdivided into 10 kb regions, and significant signals from aforementioned studies were arranged into their corresponding regions according to their genomic position. For each region, rank product values were calculated and significance values were estimated by permuting the original dataset.

RESULTS

Altogether, 179 regions (representing 33 contiguous genomic regions) had significant accumulation of signals when P-value cut-off was set at 0.0001. Identified regions with significant accumulation of signals contained 29 plausible candidate genes for PD. In conclusion, we present a novel approach for identification of candidate regions and genes for various human disorders, based on the positional integration of data across various types of omic studies.

Genotator: a disease-agnostic tool for genetic annotation of disease

BACKGROUND

Disease-specific genetic information has been increasing at rapid rates as a consequence of recent improvements and massive cost reductions in sequencing technologies. Numerous systems designed to capture and organize this mounting sea of genetic data have emerged, but these resources differ dramatically in their disease coverage and genetic depth. With few exceptions, researchers must manually search a variety of sites to assemble a complete set of genetic evidence for a particular disease of interest, a process that is both time-consuming and error-prone.

METHODS

We designed a real-time aggregation tool that provides both comprehensive coverage and reliable gene-to-disease rankings for any disease. Our tool, called Genotator, automatically integrates data from 11 externally accessible clinical genetics resources and uses these data in a straightforward formula to rank genes in order of disease relevance. We tested the accuracy of coverage of Genotator in three separate diseases for which there exist specialty curated databases, Autism Spectrum Disorder, Parkinson's Disease, and Alzheimer Disease. Genotator is freely available at http://genotator.hms.harvard.edu.

RESULTS

Genotator demonstrated that most of the 11 selected databases contain unique information about the genetic composition of disease, with 2514 genes found in only one of the 11 databases. These findings confirm that the integration of these databases provides a more complete picture than would be possible from any one database alone. Genotator successfully identified at least 75% of the top ranked genes for all three of our use cases, including a 90% concordance with the top 40 ranked candidates for Alzheimer Disease.

CONCLUSIONS

As a meta-query engine, Genotator provides high coverage of both historical genetic research as well as recent advances in the genetic understanding of specific diseases. As such, Genotator provides a real-time aggregation of ranked data that remains current with the pace of research in the disease fields. Genotator's algorithm appropriately transforms query terms to match the input requirements of each targeted databases and accurately resolves named synonyms to ensure full coverage of the genetic results with official nomenclature. Genotator generates an excel-style output that is consistent across disease queries and readily importable to other applications.