The IndyMed Preparedness Initiative:
A roadmap from Corona, Long COVID, Post-Vac to Chronic Fatigue Syndrome and P4 Family Medicine

Figures and extended legends

Figure 1 Pathogenesis and stratification of Covid-19-diseases at Intensive-Care-Units. The cartoon illustrates how in pandemic times direct to consumer (DTC) genetic testing was supposed to be combined with Corona antibody diagnostics. In the forthcoming future, the roadmap might be the following: DTC genetic testing services are ordered by individual customers, clinical and antibody testing are assumed to be performed in concert with associated Family Physician.
The extended computational data analysis of SNP and clinical data is scheduled to be conducted by trained bioinformatic expert teams that compute the most informative SNP panels with the final directive to store Corona /disease related SNP data on personal health records of the customers.
IndyMed aims to conduct a pilot study together with DTC service providers by offering this research and development (R&D) scheme to individuals that suffer from ME/CFS besides studies with focus on osteoarthritis, rheumatoid arthritis and multiple sclerosis.

Figure 2 Animated Interferon-beta-related signal transduction pathway [Hundeshagen et al. 2012; Fairley et al. 2019].
Please find the animation here: Interferon Pathway visualisation of SNPs
A Nonsynonymous coding SNPs of genes representing the Interferon signal pathway were counted to determine and illustrate SNP related complexities found between protein sequences derived from different personal genomes. The color coding (green shades) discloses how many different coding SNPs have been detected per protein and individual genome. The speed of the animation, meaning how many genomes shall be displayed consecutively to visualize the interplay of differences in polymorphic signal transduction between individuals can be manually assessed, as well the animation can be stop at any time. The SNP count is shown for one individuum (NA12045), see NA12045 in Figure 10 being link with ICU_44A4.
B Minimum spanning trees were calculated based on the number of SNPs in coding exons of 503 Caucasians provided by the 1000 genome project. The individual genome NA12045 is marked blue. The node relationship indicates how similar or dissimilar the individual´s coding SNPs are compared to the population.

Figure 3 Polygenic risk determination in genes, to determine the severity of infectious diseases e.g. SARS-CoV2 Covid19. The gene structure has been illustrated by upstream and downstream regions, 3 exonic and 2 intronic regions. Each SNP might be presented homozygous to be a disease SNP or a SNP being protective. The weighted factors F1-Fn on the RNA level (DNA based) and f1-fn on the protein level (Protein-based) are the crucial factors to determine the validity of personal risk score analysis. The formula PCRS is expected to be universally applicable. The IndyMed initiative plans to be implemented in an AI driven knowledge based expert system.

Figure 4 Roadmap P4 Family Medicine in (non-) pandemic scenarios. Personal assessments of individuals regarding the 4 Ps coined participatory (B5), personal (B6), predictive (B4) and preventive(B2) are compared to immune status of Jane & Joe Public and one’s own health by making use of the ICD10 classification. Though this illustration is being focused on Corona, the same P4 schedule can be applied for the assessment of any other infection or comorbidity. Strategic highlights are the integration of in-house knowledge on whole genome/medical history data of Wellderly /Centenarians (B1), the usage of wearables in assessing longitudinal data (e.g. physical activity, body temperature) or the integration of density peptide mapping studies and/or B-cell receptor and T-cell receptor sequencing data.

Figure 5 Transgenerational Medicine: Graphical representation of chromosomal heterozygosity by comparing the genome of a grandchild with the genomes of his maternal and paternal grandparents broken down to 23 chromosomes (numbers 1-22 and X-chromosome) based on Direct-to-Consumer-Services (23andMe). The different colors indicate shared DNA segments for grandchild and grandfather maternal (yellow), grandchild and grandmother maternal (purple), grandchild and grandmother paternal (orange), and grandchild and grandfather paternal (light blue). Numbers of half identical as well as complete identical DNA segments are given at the left for each combination.

Figure 6 IndyMed Transgenerational P4 Family Medicine healthcare initiative (SNP lineal family based GWAS approach). Inherited transgenerational traits within blood related family members are illustrated by showing the genetic inheritance of polygenic diseases (Disease SNP Candidate (DSC)) over 3 generations from Great-Grandparents maternal and paternal to their Great-Grandparents-Child (see also Figure 5). As long dominant and recessive Mendelian gene defects are traced, a simple PCR-sequence analysis will be sufficient. Note, P4 Family Medicine projects deal with the identification of polygenic disease marker and the stratification of predictive SNPs followed by a prevention strategy.

Figure 7 MHC class I peptide antigen presentation illustrated on the left: MHC class I peptide presentation to CD8 positive cytotoxic T-cells. Note, Corona viruses are taken up by ACE2 positive cells, adenoviruses by CAR and LNP mRNA vaccines by apolipoprotein E. Note, peptides presented by MHC class I complexes are of cytosolic origin. Adenoviral DNA will end up in the nucleus. Possibly, DNA fragments of DNA contaminated mRNA vaccines might enter the nucleus of dividing cells during the mitotic phase as well. Membrane bound Spike protein might be attacked by antibodies leading to antibody dependent cell-mediated cytotoxicity (ADCC).
MHC class II peptide presentation by B-cells illustrated on the right: Peptides are derived from antigens that have initially been engulfed in B-cells by membrane bound monomeric IgM (note, endothelial cells and antigen-presenting cells (APC) do not express monomeric IgM antibodies on their cell surface). Usually, B-cells require cytokines secreted by CD4 positive helper T-cells to induce IgM production, Activation-Induced Cytidine Deaminase (AID) mediated IG class switching and differentiation of antibody secreting plasma cells.

Figure 8 Vaccination study of healthcare workers.
A The antibody titers specific to SARS-CoV-2 Spike protein are listed on the left (red bars), the antibody titers specific to SARS-CoV-2 NCapsid are listed on the right (green bars) for 17 donors. Values are given in logarithmic scaling. Donor IDs are listed at the bottom.
B Regression Analysis: NCapsid antibody titers are listed at the y-axis, antibody titers regarding the Spike protein are listed at the x-axis. Parameters of the regression analysis are given in the box.

Figure 9 Outlier-analysis of CEN: A longevity-related gene-set based on 37 whole genome sequenced ICU patients, 7 healthy Europeans and one 111 years old healthy female (CEN). The dendrogram regarding the genome IDs (right side) is shown on the left. Segments of dissected gene structures (see also Figure 3) are listed at the bottom, corresponding dendrograms at the top. Please, note SNPs being heterozygous (X1), homozygous protective (X0) and disease associated (X2) classify together.

Figure 10 Undirected Graph Presentation: Network diagram visualizing the relationships of 51 individuals: 44 healthy Europeans (light blue), 6 ICU patients (yellow), and 1 CEN (green) based on the disease values of 50 SNPs. The graphs determine which genomes (nodes) are preferentially connected with each other using the 3 highest SNP values that each SNP shares with the 51 genomes selected. The SNP disease values define the connections between the individuals regarding their top three entries. The abundance of SNP connections between two genomes is illustrated by the thickness of the connecting graph. Individuals not connected to others are given at the right. Interestingly, the ICU patients are directly connected with each other coined ICU-32AB, ICU_44A4 and ICU_53A3. Genome NA12045 is linked with the ICU genome ICU_44A4, see also the animation of NA12045 in Figure 2.

Figure 11 Heatmap and clustering of 28 selected SNPs (nominator CEN: fH and P) to compare SNP data sets stratifying 37 ICU patients with the 111 years old female (CEN). Average Linkage and Euclidean distance measurement model was used. Note, unfortunately, we do not know how CEN would have managed to cope with a SARS-CoV2 infections. As such, her genome is taken as an outlier and as a surrogate in SARS-CoV-2 host genome studies. The principal concept becomes obvious. With this method, we identify a bunch of SNPs in the midst of the heatmap that are shared by 7/8 ICU patients but not by CEN. We hypothesize that this strategy will enable us to determine weighted factors to improve our prediction of personal risk scores.

Figure 12 Hypothetical model regarding the pathophysiology of ME/CFS. The illustration is an extension of Figure 7. The model is based on our publication by Lustrek et al. 2013 and published expertise on IgG trafficking [Blumberg et al. 2019; Pyzik et al. 2019; Schmidt et al. 2017; Patrick et al. 2023; Quigley et al. 2015]. Our ME/CFS model is based on our understanding that Covid-19 is a polygenic disease, but the pathophysiology of ME/CFS is autoimmune mediated and the disease process is most likely dependent on a confounder, a second trigger (Herpes virus or EBV expression, long-term expression of Corona Spike protein, remaining LNP residues in the cell, integrated DNA plasmid from DNA contaminated mRNA vaccines). Target cells (here endothelial cell) are heavily involved in IgG trafficking of IgG and albumin. As illustrated in the cartoon, the FcRn receptor takes IgG immunoglobulins together with their cargo (Antigens /Peptides) into the Sorting Endosomes. The immunoglobulins get re-cycled and the cargo peptides become degraded. Noteworthy, endothelial cells are in principle MHC class II negative. If these cells get in contact with cationic LNPs (LNPs encoded mRNA vaccines), inflammatory processes are expected to be induced followed by cellular infiltration.
Most likely, the expression of MHC class II complexes will be induced in these endothelial cells as well. Suddenly, the cargo peptides do not get degraded anymore, but they are expected to be presented to CD4 T-cells. Simultaneously, CD8 T-cells might attack the infected and/or vaccinated endothelial cells. In addition, endogenous viral proteins might get activated, or they were already reactivated before. Note, inflamed tissues do express APO-E, a target for uptake of LNP-coated mRNA vaccines. Tissues/cells with high proliferation indices do more easily integrate DNA in their genome.
In summary, the ME/CFS model presented is based on a two-step procedure. Step I: activation of CD8 cells, Step II: the activation of MHC class II peptide presentation of peptides that are delivered via the IgG trafficking. Our model distinguishes between PWM type I and PWM type II peptides [Lustrek et al 2013]. PWM type I peptides are supposed to enhance the inflammatory process (second response), PWM type II peptides should be degraded instead.

Figure 13 Generalized Preparedness-Plan using personalized agent-based infection modelling.
The preparedness plan is a result of communications that Prof. Thiesen experienced as actor /scientific expert with healthcare providers on local, regional and national levels and as follower of public and social media [Thiesen: Auswertung des Corona-Impf-Checkers; Thiesen: Ausschussdrucksache Deutscher Bundestag]. One prominent event, worth mentioning, was the talk show held by Markus Lanz on April 2nd, 2020, illustrating how in Mecklenburg-Western Pomerania experts gave advice to local political authorities [Zweites Deutsches Fernsehen: Markus Lanz]. As experienced by medical colleagues [Kremer et al. 2020], the strong age dependency of Covid-19 deaths was completely ignored in public and social media. As outlined by Glocker et al. on the preprint surfer [Glocker et al. 2021 Dec 15] and being published February 2nd, 2022 [Glocker et al. 2022 Feb 2], the shift from SARS-CoV-2 Delta to Omicron has been coined Babylonian Confusion. The Preparedness-Plan presented integrates experiences experts have made during the pandemic. The IndyMed Preparedness-Plan as presented led to tailor-made NPI measures regarding forthcoming pandemics. Unlike one-size-fits-all approaches, tailor-made plans include local factors such as cultural practices, community structures, resource availability, local health infrastructure, and specific epidemiological data in addition to detailed knowledge on impact comorbidities might have in respect to regional geographic and demographic details of a population e.g. countryside vs. metropolitan area. A democracy having such a preparedness plan would never have coined an expression such as Covidiots.

Figure 14 Risk score formulas presented cover four viewpoints:
A The risk of viral Variants of Concern that touches everyone whether putative victim or healthcare provider.
B Initial risks healthcare providers ought to protect a society from.
C The risk in case, a pandemic severely hits only a selected subgroup within a population, medical societies are called to be in charge of determining causal reasons e.g. that might determine the severity of an infection. SNP data bases are available to assess the diversity of protein structure functions within a population.
D Risk determination of altered regulation of gene expression. Here, we do not have databases that can be immediately used.
The beauty of this illustration: Experts might be encouraged to adjust the weighted factors of the individual sub-parameter mentioned, plus extend the number of sub-parameters as well - On the way to a real-world roadmap.