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October 2017

Nutritional and Metabolic Gene Status With Autism Versus Neurotypical

Children and the Association with Autism Severity

 

Introduction

Current research demonstrated a strong relationship between the genes that control nutrition and metabolic function that manifest as early childhood developmental disorders. Studies reveal low levels of biotin, plasma glutathione, RBC SAMe, plasma uridine, plasma ATP, RBC NADH, RBC NADPH, CoQ10, plasma sulfate, plasma tryptophan, dopamine, glutathione, high level of oxidative stress markers and plasma glutamate. https://doi.org/10.1186/1743-7075-8-34

 

Genes Implicated

There are many implicated genes in Autism and Neurotypical children that demonstrate possible pathway disturbances that involve key functional proteins and enzymes that control major neurotransmitters, folate metabolism and cofactors that regulate vitamin and mineral metabolism. I have listed some of these genes for review. http://www.genecards.org/Search/Keyword?queryString=autism%20and%20nutrition%20

 

RPS6KA1, ABCB1, PIK3CG, RPS27A, HIF1A, PDXK, SOD2, MUC1, NOS1, SLC1A1, GRIA3, SLC1A3, GRIA1, SLC1A2, SLC11A2, NOS2, NTS, NTRK2, APOE, L1CAM, SST, SERPINA1, SCT, HMGB1, BDNF, RPS6KB1, HMBS, AGRP, SERPINC1, SERTAD3, HMGCR, GHSR, ERBB4, HGF, SOD1, GOPC, MTRR, PCBD1, HFE, HRH1, STX1A, ADCYAP1, MAPK3, EIF4EBP1, HRH2, SLC6A4, LEP, SLC7A5, APP, SLC6A3, PIGW, ACOX1, PIK3CA, SLC19A1, SLC4A4, ALDH5A1, SLC40A1, SLC6A14, GRIA2, ALDH2, BCR, GPX1, GPRC6A, SSTR5, EP300, SETD2, PRKAA1, FLNA, CBS, CALB2, CAT, POU1F1, PSAP, CASK, FLG, IRS1, GH1, MTOR, ITGA4, BTD, GFM1, IL1RN, GNRHR, GHRL, MAP2, CDKN1B, CDKN3, CDX2, PVALB, CD40LG, NR3C1, ATF6, ERBB2, PPIG, PRL, CASP9, CCL17, MC3R, CCK, CASP3, GAD2, PSEN1, MAP1B, PRLR, ADA, MAOB, CALCA, SNCA, MC4R, ACHE, PRKAA2, CCL2, GHR, PRKG2, CD79A, MTR, PTEN, ITGB3, LEPR, DYRK1A, BLZF1, TARDBP, VDR, VCP, IL1RAPL2, IGFBP3, MAPT, TPH1, TTF2, IGF1, CALB1, CARTPT, NGF, C9orf72, CYP2C19, CYP1A2, SQSTM1, PTS, CYP2R1, CYFIP2, CP, CPA1, CYP21A2, ACE, ADRB2, AKT1, PON1, GNAQ, INS, RETN, RFC1, RET, PTK2, REG1B, COMT, CNR1, CREBBP, MDM2, RAB39B, RARB, CDKN2A, OXT, PTGS2, PAH, KCNQ1, KDR, QDPR, PYY, SREBF1, CHAT, REG1A, CHMP2B, HCRT, MECP2, POMC, DRD4, DPYD, CTSC, DAO, DCTN1, DHFR, DPP4, CTNNB1, DRD2, CSN1S1, TH, TLR4, TF, TCN2, ELN, TYMS, ALPP, ACACA, MAG, TYMP, BRCA1, IL2, IL1B, IL5, IL2RB, IL10, VEGFA, GFAP, VIP, IL2RA, XDH, NPY, ASPA, IL12A, MTHFR, FHIT, MKRN3, AR, GSTT1, ADH1C, SMARCA1, ADH1B, GSTM1, TERT, TP53, TNF, IFNA1, TREM2, GDF15, ADIPOQ, GRN, GCH1, SYP, NEFL, LHX3, LDLR, LEPQTL1, MT-ND4, MT-TL1, EXT1, IGFBP2, TSPO, ATRX, MTHFD1, TSC1, GDNF, EFS, FOXP2, HTR2C, BMPR1A, GSTP1, TGFB1, EGF, HTT, TGFA, ADH7, IFNG, TG, TPO, APC, LRP5

The genes listed above involve many system controls including; immune regulation, inflammatory control, thyroid metabolism, folate metabolism, adrenal function, choline metabolism, vitamin B12 metabolism, dopamine pathways, iron utilization, biotin and thiamine cofactor transport and intracellular folate metabolism, electrolyte and gating function, oxidative metabolism and antioxidant defense, vitamin D metabolism, cell energy regulation, glutathione metabolism, histamine mast cell control, acid / base pH balance, serotonin / tryptophan metabolism, glycemic / insulin control, leptin signaling and other important metabolic control genes.

 

There are additional genes that are involved in neuroinflammatory patterns seen in PANS (Pediatric Acute-onset Neuropsychiatric Syndrome) and PANDAS (Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections) not listed but can be an addition to any custom panel. GeneSavvy NeuroDevGS has all of the genes above and more as well as the genes implicated in PANS and PANDAS.

 

Conclusion

It is essential to do comprehensive genetic testing (preferably whole exome) to curate all phenotypes associated with these nutritional implications in order to support key functional protein pathways and develop specific actionable treatment.

 

 

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Expressed Phenotype and Epigenetic Reprogramming

Phenotype

An individual’s phenotype consists of the traits we can observe. These can include features of appearance, behavior, metabolism, immunity or anything else we can detect. Collectively, genes make up the observable phenotype. The phenotype expression can be influenced by a variety of factors and generational implications. [1]

Phenotype Expression

The phenotype is also known as the clinical expression of a specific disease. For instance, in cases of neurodevelopment disorders, Autism is an expression of the phenotype. In inherited familial high cholesterol, the expressions of the genes that control this metabolism are the phenotypes. Phenotypic abnormalities can be expressed and alterations in specific gene function observed.

Exome Sequencing

Sequencing the exome allows for identification of specific phenotypes and their gene implications. This, in turn, allows for a clear identification of implicated genes that are high risk and actionable intervention to amplify functional change that the implicated genes control.  It is crucial to understand the genotype data is markedly different in implications than phenotype data.

Exome Sequencing Excerpt From NCBI

“The human exome includes all coding nuclear DNA sequences, approximately 180,000 exons that are transcribed into mature RNA. (Note that mitochondrial DNA is not included in the exome.) Although the exome comprises only 1%-2% of the human genome, the exome contains the majority of currently recognized disease-causing variants.

Clinical exome sequencing is a laboratory test designed to identify and analyze the sequence of all protein-coding nuclear genes in the genome. Approximately 95% of the exome can be sequenced with currently available techniques. The diagnostic utility of clinical exome sequencing has consistently been 20%-30% (i.e., a diagnosis is identified in 20%-30% of individuals who were previously undiagnosed but had features suggestive of a genetic condition) [Gahl et al 2012Lazaridis et al 2016].

In the past five years, exome sequencing has increasingly become clinically available because:

  • Continuous improvements in massively parallel sequencing (also known as next-generation sequencing) and bioinformatics tools for data analysis have lowered the cost and decreased the turn-around-time;
  • Reports of clinically actionable results have led to improved insurance coverage [Lazaridis et al 2016].”[2]

23andMe and Genotype

23andMe is an example of identification of a genotype. This identification is known as a single nucleotide polymorphism also known as a SNP. Simply the genotype is the set of genes that a person carries and the phenotype is the expression of observable characteristics, for example, expressed color of eyes or an expressed component of a disease or disorder. (https://www.youtube.com/watch?v=lYAHx7NiF3g). When an individual decides to analyze their genotype they are just identifying their gene set. Genotype identification is not sequencing it is just a typing analysis. It doesn’t sequence the gene or the entire exome.

Epigenetic Programming and Adaptation   

Epigenetics is the study of heritable changes in gene expression (active versus inactive genes) that does not involve changes to the underlying DNA sequence — a change in phenotype without a change in genotype —, which in turn affects how cells read the genes.

Conrad H. Waddington[3] coined the term “epigenetics,” to demonstrate that there are heritable influences on phenotype expression and predisposition to disease. Epigenetics is quickly growing and with it the understanding that both the environment and individual lifestyle can also directly interact with the genome to influence epigenetic change and adaptation.[4] The advances in epigenetics has led to new findings about the relationship between epigenetic changes and a host of disorders including various cancers, mental retardation associated disorders, immune disorders, neuropsychiatric disorders and pediatric disorders.[5]

Preferred First Line Testing

Exome Sequencing is the preferred first line analysis that will identify high-risk phenotypes involved in disease process. This analysis will assist in identifying the necessary lab testing and avoid unwarranted expensive lab workup and move to specific diagnostic testing.

Knowing the phenotype variations is essential in actionable and targetable approaches to be specific in influencing epigenetic transcript messages that increase the likelihood of high risk mutations associated with many disease states. Epigenetic reprogramming depends upon definitive identification of phenotypes associated with high-risk gene mutations that alter functionality of key proteins that control the individual specialized cells and multi-systems of the human body.

Summary

In summary, the main theme of this white paper outlines the value of exome sequencing analysis over genotyping and genome sequencing. This should be considered as a first line in determining targeted approaches to treatment. With the increasing sophistication of bioinformatics analysis the development of specialized phenotype identification panels will allow the physician to clinically treat specified phenotype targets increasing favorable outcomes in the treatment of specific diseases and disorders associated with the expressed phenotype / gene variants.

Patients will have personalized molecular approaches that can significantly influence recovery from chronic illnesses, thereby extending longevity, decreasing aging risk and preventing the serious consequences of disease.[6]

 

 

 

 

 

 

[1] Orgogozo, V., Morizot, B., & Martin, A. (2015). The differential view of genotype–phenotype relationships. Frontiers in Genetics6, 179. http://doi.org/10.3389/fgene.2015.00179

[2]https://www.ncbi.nlm.nih.gov/books/NBK279899/#app5.Background_Information_on_Exome_Seq

[3] Waddington C.H. “The epigenotype”. Endeavour 1: 18–20 (1942)

[4] Egger G. et al. Epigenetics in human disease and prospects for epigenetic therapy. Nature 429, 457-463 (2004).

[5] Jirtle R.L. and Skinner M.K. Environmental epigenomics and disease susceptibility. Nature Reviews Genetics 8, 253-262 (2007).

[6] https://www.omicsonline.org/epigenetic-therapy-in-malignant-and-chronic-diseases-2153-0645.1000118.php?aid=18923