Apps

  • Rhythmus – prescribing clarity

    Rhythmus is a new app that makes prescribing natural agents simpler than before when using the Opus23 database of natural agent effects on genes.

    Taking an overview of all SNPs for the client, the main Rhythmus screen shows a list of genes sorted by combined SNP effect power factor, with the color scheme of orange for overall downregulated and green for overall upregulated genes. With over 7,800 individual associations of genes and natural agents in the database, all based on and hyperlinked to PubMed published studies, Opus23 makes visualisation simple for the genes with the highest editor-defined power factor and with associated natural agents that affect the gene function.

    Rhythmus Prescribing App

    Taking the Agency app one step further, Rhythmus also includes the gene visualising ability of Powerspot to help the practitioner choose the best agents for the clientThe AI Pre fills the option of upregulating or downregulating the gene function and the effect required from the agents (although these can be changed manually if required). The numbers of agents associated with the gene function is also listed.

    Rhythmus can be used by checking some genes and other options, then click the Run Rhythmus button. The result is a network map of the genes in the query along with the natural agents that influence their function.

    Rhythmus network map

    The relative size of the agent indicates the confidence of the effect on the gene, and as with other network maps on Opus23, clicking on the gene or agent opens a popup for that element, from where it can be curated to the Client Report or the Protocol Report.

    The AI saves time in selecting the best options according to the available data, but this can alway be overridden by the practitioner, who may have other information about the client. Opus23 subscribes to the philosophy of ‘TMTOWTDI’ (There’s more than one way to do it, pronounced ‘Tim Toady’.) The program was designed with this idea in mind, in that it ‘doesn’t try to tell the practitioner how to parse the data.’ Rather, it presents many different frameworks and cross-sections of the available client data, using a myriad of infographic treatments. Therefore Rhythmus also offers the practitioner a user-defined alternative visualisation of up to five manually entered genes, again with an up- or downregulatory effect and the required effect size. The user-defined visualisation gives a Manhattan map of the combined effect of the possible agents, similar to one side of the Psychic app.

    Result of the user-defined selection in Rhythmus

    As before, clicking on the agent opens the agent popup, where it can be curated. Rhythmus takes Opus23 to another level of utility for data mining and analysing its huge database of PubMed-based gene-agent interactions.

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  • Three new interactive networks

    We’ve added new mapping networks to Opus 23 MAPPER app. The MAPPER app allows you to visualize your client’s genomic data directly in a number of hand-curated pathway maps. In addition to allowing for quick pattern recognition, MAPPER uses combinatorics and graph theory to ascertain certain functional characteristics of genes in the network, based on their position in a web of interconnections. All gene nodes in MAPPER trigger extensive information popup windows.

    TSH Signaling Network

    tsh

    Human thyroid stimulating hormone (TSH) is a glycoprotein secreted by the anterior part of the pituitary gland. TSH plays an important physiological role in the regulation of the hypothalamic-pituitary-thyroid axis by modulating the release of the thyroid hormones from the thyroid gland. TSH is mainly expressed in adenohypophysis , thyroid gland, leukocyte, pituitary gland, stratum basale, stratum corneum, stratum granulosum, stratum spinosum and keratinocyte. Impairment of TSH signal transduction pathway leads to thyroid disorders such as goitre, hypothyroidism and hyperthyroidism, with complex clinical manifestations. T

    Endoplasmic Reticulum Stress and Unfolded Protein Response

    upr

    The endoplasmic reticulum (ER) is a dynamic intracellular organelle with multiple functions essential for cellular homeostasis, development, and stress responsiveness. In response to cellular stress, a well-established signaling cascade, the unfolded protein response (UPR), is activated. This intricate mechanism is an important means of reestablishing cellular homeostasis and alleviating the inciting stress. Now, emerging evidence has demonstrated that the UPR influences cellular metabolism through diverse mechanisms, including calcium and lipid transfer, raising the prospect of involvement of these processes in the pathogenesis of disease, including neurodegeneration, cancer, diabetes mellitus and cardiovascular disease. [PMC3039444]

    AR Signaling Network

    ar

    Androgens, mainly testosterone and 5alpha-dihydrotestosterone (DHT) play significant role in the growth and development of the male reproductive organs. AR is found to be expressed in a number of tissues and cells including prostate, testis, seminal vescicle, epididymis, skin, skeletal muscle, cardiac muscle, liver and central nervous system. The androgen receptor is known to bind to many co-regulators at different time points and in different cell types. This DNA protein complex triggers the expression of various target genes that are associated with the male phenotype. Androgen receptors are known to induce apoptosis under certain conditions. Various regulators that regulate androgen induced apoptosis include BRCA1 and Smad3 and Akt. Mutation in AR are also known to be associated in a number of diseases including spinal and bulbar muscular atrophy (SBMA) or Kennedy’s disease and Androgen Insensitivity syndrome (AIS). Abnormal amplification of the androgen gene as well as deregulation of AR gene expression have been shown to be associated with prostate cancer.

    To learn more about Opus23 training webinars, click here.

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  • Utopia: Advice, Intelligent interface with Opus23

    Advice: Intelligent Interface with OPUS23

    ADVICE is an app in Utopia that gives algorithmic considerations of multiple bacterial strains in conjunction with the client’s own genome to provide true/false clinical outcomes. ADVICE automatically pulls the client’s Opus23 genetic data where relevant, and incorporates it into algorithmic calculations. (comparable to LUMEN in Opus23).

    Getting around ADVICE

    From the Utopia drop down menu, hover over ‘Algorithms’ until a second list appears, then select ‘Advice’. You are presented with a list of algorithms, those that are true are at the top and display the word ‘TRUE’ in a green box, followed by those that are false, which display the word ‘FALSE’ in an orange box. Each algorithm will display the repute (risk, benefit or neutral), and the magnitude. If an algorithm suggests prescriptive metabolites which enhance or reduce specific bacteria, they will be listed under Encourage or Discourage.

    The client’s relevant genes will be displayed beneath the listed ‘microbiota’ information in the same format found in the Opus23 LUMEN app. Clicking on the colored semicircle will open a pop-up window with a description of the gene and giving details of the client’s SNPs for the gene from their Opus23 data.

    Utopia Advice algorithm

    An ADVICE algorithm for gluten-induced immunopathology

    All metabolites and taxa are clickable. Clicking a metabolite opens a pop-up window with a list of bacteria affected by it. Clicking a bacterium opens a pop-up window as described in previous apps. To add an algorithm to the client report, click on the ‘Add/ Uncurated’ button.

    Individual genera may also be curated and added to the client report for the current dataset by selecting the taxon to open its pop-up information and then clicking the ‘Add/Uncurated’ button.

    Screen shot of Metabolomics pop-up window

    Pop-up window in ADVICE showing metabolomics information

    Using the Algorithm Aggregate Analysis

    At the bottom of the page is the Algorithm Aggregate Analysis. This is a summary of all advice for the client listed under either an ‘increase’ and ‘decrease’ section heading. Each section provides both the microbiota and beneficial/ harmful metabolites that are suggested to be increased or decreased by your client. The ‘result’ information can be a useful tool for streamlining complex treatment strategies. Each metabolite listed in the Algorithm Aggregate Analysis details whether or not the metabolite has mixed results (included as both encourage and discourage in ADVICE algorithms), and whether it is specific to an algorithm.

    Algorithm Aggregate Analysis screenshot

    Algorithm Aggregate Analysis for the ADVICE app

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  • Utopia: Pansophia, sequential outcome analysis

    PANSOPHIA – sequential outcome analysis

    The genomic DNA analysis software Opus 23 includes the Utopia suite of apps for analyzing sequential uBiome data, comparing sequencing-based clinical microbiome data with the client’s own genomic DNA.

    Utopia logo

    PANSOPHIA is an Utopia app that gives you the power to sort your client’s data based upon associations with health and disease as well as several other useful categories including keystone, probiotic, core species and butyrate production.  For those clients who have more than one data sample, PANSOPHIA allows you to visualize treatment progress in a graphical format that can be easily added to your client’s report.

    Navigating PANSOPHIA

    pansophia

    From the Utopia drop down menu, hover over ‘analytics’ until a second list appears, then select PANSOPHIA. You will then be presented with the default table which shows ‘everything’ and is sorted by ‘rank’ or ‘percent’.

    At the bottom of the window is a jump screen that allows you to move from one screen to the next. You can control how many rows to display be selecting an option from the ‘Show’ pull down menu. The default is 15.

    Pansophia initial screen

    Filtering and sorting results

    PANSOPHIA allows you to parse the taxon data based upon desired treatment goals. Taxa are sortable by benefit as well as pathogenic potential.  There are two ways to filter the data.

    Using category tabs:

    You can use the category tabs at the top of app’s main screen to select taxa grouped by their associations with health and disease. Once a category is selected, the information will be displayed in graph form.

    Pansophia screenshot

    The PANSOPHIA graph uses the following symbols:

    • An orange dot  denotes average %, the bar graphic represents the client data- specific %
    • For those with multiple data sets, a blue diamond denotes % change

    Click on any desired taxon to open up its information pop—up window for detailed information including taxonomy, an overview of known disease or health benefit associations, interactions and metabolomics. Click ‘add/ curate’ to include it in your clients report. Additionally, the graph itself can be printed or added to your client’s report.

    Using individual taxon selections:

    From the main screen, you can sort the taxa by ‘name’ or ‘client %’ then select desired taxa individually using the display box selections on the left hand side of the screen.  Once you have made your selections, click the orange ‘display selections’ button at the top of the screen. The individual taxon information will be displayed in graph form. Click ‘add/curate’ to include the graph in your client’s report.

       

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  • Utopia Demonstration Video

    Dr. Peter D’Adamo and Dr. Tara Nayak present an introduction to Utopia, the free microbiome analysis add-on module to Opus 23 for uBiome test results.

     

    To use Utopia, you will need to  have your client’s 23andMe data already uploaded to Opus 23. You can then upload as many raw data files from uBiome tests as you have for that client. Utopia will work with individual uBiome tests, referencing the client’s 23andMe results where appropriate, and also give sequential analysis for multiple uBiome tests.

    The unique combination of Opus 23 and Utopia make this an opportunity for practitioners to get deep insight into their clients on both a genomic and a microbiological level, all sourced from published medical literature. The interaction between the two genomic analyses provides unparalleled informatics tools, and gives the practitioner an edge over any other genomic analysis tool available today.

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  • Utopia: Spectrum, visual community organization

    SPECTRUM: Visual community organization

    Utopia logo

    SPECTRUM provides a visual representation of the taxonomic data at both the genus and phylum levels. The app demonstrates the weight, influence and diversity of your client’s microbiome in two helpful display formats, each of which are clickable for a deeper look and easy report curation.

    Navigating  SPECTRUM

    Spectrum logo

    From the Utopia drop down menu, hover over ‘analytics’ until a second list appears, then select SPECTRUM.  Phyla and genus are displayed in pie chart format, which is accompanied by the spectrum profiler found below.

    The pie charts follow the color-coding conventions found in OPUS23 indicating beneficial, neutral as well as pathogenic organisms. Click on any desired section to open up its information pop—up window for detailed information including taxonomy, an overview of known disease or health benefit associations, descendants and metabolomics. Click ‘add/ curate’ to include it in your client’s report.

    Spectrum pie charts

    The spectrum profiler demonstrates the trends in your client’s biome diversity in a graphical format. Clicking on any of the category headings will open a pop-up window listing the organisms found in your client’s sample. Each genus listed is also clickable, opening a pop-up window for detailed information, including taxonomy, an overview of known disease or health benefit associations, descendants and metabolomics. Click ‘add/ curate’ to include it in your client’s report.

    Screenshot of Spectrum Profiler

    Metabolomics is a powerful addition to the spectrum profiler that provides a comprehensive list of metabolites associated with GI biome species. A list of all metabolites active in your client is included. Click on an individual metabolite for detailed information, including genera that are enhanced, inhibited, and those which generate the metabolite as an end product. Click on the Metabolomics link to open a pop-up with all active and inactive genera.

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  • Utopia: Loam, a fertile soil

    Announcing the launch of Utopia, the suite of apps within Opus 23 that analyzes and reports on sequential data from uBiome tests. uBiome is the world’s first sequencing-based clinical microbiome screening test, giving the user insight into the bacterial population of multiple body areas. Utopia recognizes all bacteria found by uBiome, but is specifically interested in the gut bacteria and its interaction with the client’s own genomic DNA. Utopia is free for existing clients: Once you have uploaded 23andMe raw data for your client, you can add as many uBiome tests as you want for that client without additional charge. Utopia will then give you access to multiple apps to analyze the data and reference it to the client’s genomic data where appropriate.

    Utopia logo

    LOAM: Adaptable taxon data

    LOAM is a highly flexible search and sort tool that allows you to easily navigate through your client’s Ubiome results by taxon. LOAM allows you to filter taxonomic data based upon several useful parameters as well as sort the filtered results. It is similar to the ARGONAUT app in Opus 23.

    loam

    Navigating LOAM

    From the Utopia drop down menu, hover over ‘analytics’ until a second list appears, then select LOAM. You will then be presented with the default table which shows ‘everything’ and is sorted by ‘repute’ or ‘interpretation’.

    At the bottom of the window is a jump screen that allows you to move from one screen to the next. You can control how many rows to display be selecting an option from the ‘Show’ pull down menu. The default is 15.

    Loam Screenshot

    Filtering and sorting results

    LOAM allows you to parse the taxon data based upon desired treatment goals. Taxons are sortable by benefit as well as pathogenic potential.

    The LOAM table displays the following data by column:

    • Taxon name
    • Repute, displaying beneficial !, neutral ! and pathogenic ! 
    • Rank
    • Client-specific % population
    • Average % (if available)
    • Standard deviation (if available)
    • Interpretation (displayed up to +6 times the standard deviation, populations found in a greater abundance are indicated by )
    • Normal variance
    • Order magnitude

    Click on any desired taxon to open up its information pop—up window for detailed information including taxonomy, an overview of known disease or health benefit associations, interactions and metabolomics. Click ‘add/ curate’ to include it in your clients report. The Curated column will then show a green checkmark against all curated taxon after refreshing the page. 

    LOAM columns are sortable. Click on any column title to sort by that column. Click that column again to reverse the sort order.

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  • Protection against risk of Parkinson’s disease

    Parkinson’s disease was described in 1817 by Dr James Parkinson, who published an essay reporting six cases of ‘paralysis agitans’ (the disorder that was later renamed after Parkinson). He described the characteristic resting tremor, abnormal posture and gait, paralysis and diminished muscle strength, and the way that the disease progresses over time. [1]

    Since the advent of genetic testing several genes have been found to be associated with Parkinson’s disease (PD), resulting in various classifications. Autosomal dominant Parkinson disease type 8 (PARK8) is caused by heterozygous mutation in LRRK2, the gene encoding the dardarin protein. [2] The G2019S variant is one of the most common genetic causes of PD. Although the clinical motor signs of PD in carriers of the G2019S mutation are largely typical, an earlier age at onset of motor symptoms has been reported in some studies. [3]

    The word dardarin was taken from a Basque word for tremor, as the gene was first identified in families from England and the north of Spain. Mutations in LRRK2 are the most common known cause of familial and sporadic PD, accounting for approximately 5% of individuals with a family history of the disease and 3% of sporadic cases. They account for up to 10% of autosomal dominant familial and 3.6% of sporadic PD. More than 40 different variants, almost all missense, have been found. Seven seem to be proven pathogenic mutations, and are clustered in functionally important regions which are highly conserved through evolution. [4]

    23andMe carried out a privately-funded genome-wide association study (GWAS) to search for novel genetic variants associated with PD. The results, which were published in PLOS in 2011, replicated existing associations and discovered two novel variants. [5] In addition, 23andMe researched genes conferring protection on those with high-risk genes. [6] They found that of the approximately 1 in 10,000 people who have the G2019S  variant, those who also had a mutation in SGK1 were found to have a lower risk of PD than those with just the G2019S variant, conferring protection against the increased risk of PD. [7]

    Other causes of, or factors contributing to PD include pesticide exposure, [8] head trauma, medication, prolonged oxidative stress from infection or high homocysteine. Genetic factors include increased function of MAOB enzymes, high histamine from HNMT mutations, elevated L-dopa from DDC mutations or B6 deficiency. The Opus 23 software contains algorithms for Parkinson’s disease associated with some of these genetic causes, risk or contributory factors found in the 23andMe raw data. A new algorithm added to the Opus 23 Lumen app looks for both the LRRK2 G2019S and the SGK1 variants to assess for both risk of PD and protection from the risk genotype, and lists natural agents associated with gene function.

    References:

    1. Parkinson J. An essay on the shaking palsy. London: Sherwood, Neely and Jones; 1817.
    2. Kachergus J, Mata IF, Hulihan M, et. al. Identification of a novel LRRK2 mutation linked to autosomal dominant parkinsonism: evidence of a common founder  across European populations. Am J Hum Genet. 2005 Apr;76(4):672-80. Epub 2005 Feb 22. PMCID: PMC1199304.
    3. Thaler A, Mirelman A, Gurevich T,  et. al. Lower cognitive performance in healthy G2019S LRRK2 mutation carriers. Neurology. 2012 Sep 4;79(10):1027-32. PMCID: PMC3430708.
    4. Davie CA (2008). “A review of Parkinson’s disease”. Br. Med. Bull. 86 (1): 109–27. PMID 18398010
    5. Do CB, Tung JY, Dorfman E, et. al. Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson’s disease. PLoS Genet. 2011 Jun;7(6):e1002141. PMCID: PMC3121750
    6. 23andMe Blog: 23andMe Discovers Genetic Variant That May Protect Those at High Risk for Parkinson’s Disease. Accessed Aug 28, 2016.
    7. Polymorphisms associated with Parkinson’s disease. Patent US8187811 B2.
    8. Van Maele-Fabry G, Hoet P, Vilain F, Lison D. Occupational exposure to pesticides and Parkinson’s disease: a systematic review and meta-analysis of cohort studies. Environ Int. October 2012, 46: 30–43. PMID: 22698719.

     

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  • Kava-kava for panic attacks

    A 2008 paper by Thoeringer et. al., published in the Journal of Neural Transmission [1] described a study of 238 adult Caucasian patients recruited from an Anxiety Disorders Outpatient Clinic in Europe presenting various anxiety disorders, including panic disorder, agoraphobia, social phobia and generalized anxiety disorder. As there are many genetic studies linking the GABA system to anxiety disorders and related personality traits, the patients were genotyped for various polymorphisms in the SLC6A1 (GABA transporter 1), along with 267 controls without anxiety disorder.

    Five polymorphisms in SLC6A1 or in the promoter region were found to be nominally associated with anxiety disorders. Although none were statistically significant alone, the authors found a significant combined effect of all investigated polymorphisms, which strongly suggested a major role of SLC6A1 in the genetic susceptibility of pathological anxiety. Looking at patients with panic disorder, those with the most severe panic disorder were significantly more likely than controls to have two related polymorphisms in the SLC6A1.

    GABA (gamma-aminobutyric acid) is a neurotransmitter that decreases activity in the neurons of the brain and inhibits the excitability of nerve cells. Drugs that block the GABA transporter molecule inhibit the removal of GABA from the nerve synapses, thereby prolonging the action of GABA. Tiagabine, a selective GABA transporter 1 blocker, is used as an antiepileptic, but has off-label use for anxiety disorder. This is thought to be due to the augmentation of GABA function as a neurotransmitter in the brain. This drug has side-effects, however, and other methods of reducing panic disorder have been investigated.

    Kava-kava (Piper methysticum) is a traditional plant-based medicine found in the Western Pacific region which has been shown to reduce anxiety. Kava-kava is legal in most countries, and is generally safe when the root from a ‘noble’ cultivar is used. A study of kava-kava for anxiety reduction using the Hamilton Anxiety Rating Scale (HAMA) as the primary outcome found that patients with generalized anxiety disorder who had polymorphisms in SLC6A1 and in the 5′ flanking region potentially responded to kava-kava supplementation with a more significant reduction in HAMA rating than in patients without the polymorphisms. [2] Treatment consisted of tablets standardized to contain 60 mg of  kavalactones per tablet for a total daily dose of 120 mg of kavalactones for the first 3-week controlled phase, being titrated to 240 mg of kavalactones in nonresponse at the 3-week mark for the second 3-week controlled phase, or placebo.

    An algorithm in the Lumen app in Opus 23 determines how many relevant SNPs a client has in SLC6A1 that are reported in their 23andMe raw data, and which may make treatment with kava-kava more effective in reducing anxiety disorder and panic symptoms.

    References:

    1. Thoeringer, C.K., Ripke, S., Unschuld, P.G. et al. The GABA transporter 1 (SLC6A1): a novel candidate gene for anxiety disorders. J Neural Transm (2009) 116: 649. doi:10.1007/s00702-008-0075-y. PMCID: PMC2694916
    2. Sarris J, Stough C, Bousman CA, et.al. Kava in the treatment of generalized anxiety disorder: a double-blind, randomized, placebo-controlled study. J Clin Psychopharmacol. 2013 Oct;33(5):643-8. doi: 10.1097/JCP.0b013e318291be67. PMID: 23635869
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