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Genetic Influence on Thyroid Stability

Many people suffer the effects of thyroid disease which include hypothyroidism, hyperthyroidism, Grave’s disease, Hashimoto’s thyroiditis (autoimmune thyroiditis), generalized thyroid inflammation and thyroid cancer.

Unrelated human subjects share 99.9% of their genome. It has been estimated that 90% of the remaining variation is accounted for by approximately 10 million common single nucleotide polymorphisms (SNPs), single base changes spread throughout the genome. These are very useful in studying gene-phenotype associations as they occur commonly in the general population, and may either cause changes in gene function themselves, or more frequently are markers of nearby elements that do.

Genetics play a prominent role in both determination of thyroid instability and increased disease risk. Heritability studies have suggested that up to 67% of circulating thyroid hormone and TSH concentrations are genetically determined, suggesting a genetic basis for narrow intra-individual variation in levels, perhaps a genetic ‘set point’.

Thyroid hormones play an essential role in normal human physiology with effects on almost all tissues to influence growth and development, maintain normal cognition, cardiovascular function, bone health, metabolism and energy balance. With increasing research in genetic implications we understand the important influence that genetics play in normal and abnormal thyroid function.  There is also strong connection in utilization and conversion of thyroid hormones in thyroid instability and there are certain genes that are involved in this conversion, for example, DIO1, DIO2, DIO3 are all involved.

Some genes known to influence thyroid function, including iodothyronine deiodinase 2 and the TSH receptor, have been shown to influence a wide range of clinical and developmental phenotypes from bone health to neurological development and longevity; such observations will help us understand the complex action of thyroid hormones on individual tissues.

Autoimmune thyroid disease commonly runs in families, and the search for genes that increase susceptibility has identified several good candidates, particularly those involved in immune regulation and thyroid function. However, these genes alone account for only a small percentage of the current prevalence of these disorders. Although the advancement of genetic technology has led to many significant findings in the last two decades, it is clear that we are only just beginning to understand the role of genetics in thyroid function and disease.[1][2][3][4][5][6][7][8][9]

There are many genes / variants that are integrally involved in thyroid function and regulation and key genes listed below are associated with thyroid functional changes.

Thyroid Top Gene List:

ABCD1, ADA, ADH7, AHCY, AIRE, AITD1, AITD2, AITD4, AKT1, AOX1, ATP5O, AVP, BAX, BGLAP, BMPR1A, C1QA, C1QB, C1QC, C1R, C1S, C2, C3, C4A, C4B, CALCA, CAPZB, CASP8, CBS, CCNA2, CCNB1, CCND3, CD163, CD1A, CD28, CD40, CD58, CD69, CD80, CDKN1B, CDKN2A, CDKN2B, CDKN3, CGA, CHKB, COL1A1, COMT, COQ2, COQ3, COX5A, COX6C, CRH, CRP, CSF1, CTLA4, CXCL8, CYP11A1, CYP17A1, CYP21A2, CYP27B1, DDC, DIO1, DIO2, DIO3, DUOX2, DUOXA2, EDN1, ENO1, FAS, FASLG, FCGR2B, FCRL2, FCRL3, FOXD3, FOXE1, FOXP3, GAD1, GAD2, GH1, GHR, GLIS3, GNAS, GPR174, GPX1, GPX3, GSTM1, GSTM3, GSTP1, HLA-A, HLA-B, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DRB4, HRAS, HSPD1, HT, ICAM1, ICAM3, IFIH1, IFNA1, IFNB1, IFNG, IFNG, IGF1, IGFBP1, IGFBP3, IGSF1, IL10, IL15, IL16, IL17A, IL18, IL1B, IL1R1, IL1RN, IL2, IL22, IL23R, IL2RA, IL2RB, IL4, IL5, IL6, IL7, IL7R, INS, ITPR3, IYD, LEP, LTA, MAOA, MAOB, MAP2K1, MBL2, MC2R, MET, MIF, MTHFR, NCOA4, NKX2-1, NKX2-5, NOS1, NOS2, NOS3, ODC1, PAX8, PDE8B, PICALM, PIK3CA, PLCG2, POMC, POU1F1, PRL, PROP1, PRSS3, PTEN, PTPN22, PTPRC, REN, RYR1, S100B, SCGB3A2, SECISBP2, SELENOS, SERPINA7, SERPING1, SHBG, SIRT1, SLC16A2, SLC1A4, SLC26A4, SLC30A8, SLC3A2, SLC5A5, SLCO1C1, SOD2, STAT3, TFAM, TG, TGFB1, THRA, THRB, TLR3, TMPO, TNF, TNFRSF11B, TNFSF13B, TP53, TP63, TPO, TRAF1, TRAP1, TRHR, TRPV1, TSHB, TSHR, TTR, VDR, VEGFA, ZFAT

 

Signs and Symptoms of Hypothyroidism

  • Fatigue
  • Increased sensitivity to cold
  • Constipation
  • Dry skin
  • Weight gain
  • Puffy face
  • Hoarseness
  • Muscle weakness
  • Elevated blood cholesterol level
  • Muscle aches, tenderness and stiffness
  • Pain, stiffness or swelling in your joints
  • Heavier than normal or irregular menstrual periods
  • Thinning hair
  • Slowed heart rate
  • Depression
  • Impaired memory
  • Anxiety

 

Signs and Symptoms of Hyperthyroidism

  • Sudden weight loss, even when your appetite and the amount and type of food you eat remain the same or even increase
  • Rapid heartbeat (tachycardia) — commonly more than 100 beats a minute — irregular heartbeat (arrhythmia) or pounding of your heart (palpitations)
  • Increased appetite
  • Nervousness, anxiety and irritability
  • Tremor — usually a fine trembling in your hands and fingers
  • Sweating
  • Changes in menstrual patterns
  • Increased sensitivity to heat
  • Changes in bowel patterns, especially more frequent bowel movements
  • An enlarged thyroid gland (goiter), which may appear as a swelling at the base of your neck
  • Fatigue, muscle weakness
  • Difficulty sleeping
  • Skin thinning
  • Fine, brittle hair

Signs and Symptoms of Grave’s Disease

  • Anxiety and irritability
  • A fine tremor of your hands or fingers
  • Heat sensitivity and an increase in perspiration or warm, moist skin
  • Weight loss, despite normal eating habits
  • Enlargement of your thyroid gland (goiter)
  • Change in menstrual cycles
  • Erectile dysfunction or reduced libido
  • Frequent bowel movements
  • Bulging eyes (Graves’ ophthalmopathy)
  • Fatigue
  • Thick, red skin usually on the shins or tops of the feet (Graves’ dermopathy)
  • Rapid or irregular heartbeat (palpitations)

 

Signs and Symptoms of Hashimoto’s Thyroiditis (Thyroid Autoinflammation)

  • Fatigue and sluggishness
  • Increased sensitivity to cold
  • Constipation
  • Pale, dry skin
  • A puffy face
  • Brittle nails
  • Hair loss
  • Enlargement of the tongue
  • Unexplained weight gain
  • Muscle aches, tenderness and stiffness
  • Joint pain and stiffness
  • Muscle weakness
  • Excessive or prolonged menstrual bleeding (menorrhagia)
  • Depression
  • Memory lapses

 

Signs and Symptoms of Thyroid Cancer

  • Neck pain:In many cases, neck pain starts in the front. In some cases the neck pain may extend all the way to the ears.
  • Voice changes:Experiencing hoarseness or other voice changes that do not go away could be a sign of thyroid cancer.
  • Breathing problems:Sometimes thyroid cancer patients say it feels like they are breathing through a straw. This breathing difficulty is often a symptom of the disease.
  • Coughing:A cough that continues and is not related to a cold.
  • Trouble swallowing:A growth or nodule on the thyroid gland may interfere with swallowing.

There are many genes  / variants implicated in thyroid cancer, but to name a few:

APC, CDC73, DICER1, MEN1, PRKAR1A, PTEN, RET, SDHB, SDHD, TP53, WRN

 

Conclusion

The ThyroidStabilityGS genetic panel curates gene relationships for hypothyroidism, hyperthyroidism, thyroid inflammation, Hashimoto’s thyroiditis, autoimmune thyroiditis and thyroid cancer risk for a more focused diagnosis and targeted treatable action plan.

 

Additional Resources:

  1. Thyroid Cancer Survivors
  2. Association Butterfly Thyroid Cancer Trust
  3. BHD Foundation
  4. National Parathyroid Education Foundation Pheo Para Troopers
  5. Association for Multiple Endocrine Neoplasia Disorders International Registry of Werner Syndrome
  6. NORD – Birt-Hogg-Dube Syndrome
  7. NORD – Carney Complex
  8. NORD – Familial Adenomatous Polyposis NORD – Pheochromocytoma
  9. NORD – Multiple Endocrine Neoplasia Type 2 NORD – Werner Syndrome
  10. Gene Reviews – Birt-Hogg-Dube Syndrome
  11. Gene Reviews – Carney Complex
  12. Gene Reviews – APC-Associated Polyposis Conditions
  13. Gene Reviews – Hereditary Paraganglioma-Pheochromocytoma Syndromes Gene Reviews – Li-Fraumeni Syndrome
  14. Gene Reviews – Multiple Endocrine Neoplasia Type 2
  15. Gene Reviews – Werner Syndrome

 

[1] Hansen PS, Brix TH, Sørensen TI, Kyvik KO, Hegedüs L. Major genetic influence on the regulation of the pituitary-thyroid axis: a study of healthy Danish twins. J Clin Endocrinol Metab. 2004;89:1181–7.[PubMed]

 

[2] Samollow PB, Perez G, Kammerer CM, Finegold D, Zwartjes PW, Havill LM, et al. Genetic and environmental influences on thyroid hormone variation in Mexican Americans. J Clin Endocrinol Metab. 2004;89:3276–84.  [PubMed]

 

[3] Meikle AW, Stringham JD, Woodward MG, Nelson JC. Hereditary and environmental influences on the variation of thyroid hormones in normal male twins. J Clin Endocrinol Metab. 1988;66:588–92.  [PubMed]

 

[4] Andersen S, Pedersen KM, Bruun NH, Laurberg P. Narrow individual variations in serum T(4) and T(3) in normal subjects: a clue to the understanding of subclinical thyroid disease. J Clin Endocrinol Metab. 2002;87:1068–72.  [PubMed]

 

[5]  Panicker V, Wilson SG, Spector TD, Brown SJ, Falchi M, Richards JB, et al. Heritability of serum TSH, free T4 and free T3 concentrations: a study of a large UK twin cohort. Clin Endocrinol (Oxf) 2008;68:652–9.  [PubMed]

 

[6]  de Jong FJ, Peeters RP, den Heijer T, van der Deure WM, Hofman A, Uitterlinden AG, et al. The association of polymorphisms in the type 1 and 2 deiodinase genes with circulating thyroid hormone parameters and atrophy of the medial temporal lobe. J Clin Endocrinol Metab. 2007;92:636–40.  [PubMed]

 

[7] Panicker V, Saravanan P, Vaidya B, Evans J, Hattersley AT, Frayling TM, et al. Common variation in the DIO2 gene predicts baseline psychological well-being and response to combination thyroxine plus triiodothyronine therapy in hypothyroid patients. J Clin Endocrinol Metab. 2009;94:1623–9.  [PubMed]

 

[8] van der Deure WM, Appelhof BC, Peeters RP, Wiersinga WM, Wekking EM, Huyser J, et al. Polymorphisms in the brain-specific thyroid hormone transporter OATP1C1 are associated with fatigue and depression in hypothyroid patients. Clin Endocrinol (Oxf) 2008;69:804–11.  [PubMed]

 

[9] Vaidya B, Kendall-Taylor P, Pearce SH. The genetics of autoimmune thyroid disease. J Clin Endocrinol Metab. 2002;87:5385–97.  [PubMed]

 

Gene Patterns of Chronic Migraine Headaches

 

Migraines Are Heritable

Gene patterns in migraine headaches demonstrate strong association with sensitivity and susceptibility in families. Migraine headaches are known to cluster in families and have long been considered to be an inherited disorder. Migraine, with aura or without aura, has a substantial risk of familial occurrence, and genetic epidemiologic studies suggest that migraine without aura and migraine with aura have distinct and unique heritability. Twin studies reveal that approximately one half of the variation in migraine is attributable to additive genes, while the remainder is caused by unshared rather than shared environmental factors between twins. [1]

Complex segregation analyses (CSA), a technique within genetic epidemiology to determine whether there is evidence that a major gene underlies the distribution of a given phenotypic trait, have demonstrated that a multifactorial heredity model, wherein multiple genetic susceptibility factors interact with multiple environmental factors and render an individual susceptible to recurrent attacks, is most compatible with the mode of inheritance of migraine.[2] Migraine, like many complex multifactorial inherited diseases, is co-transmitted with other disorders. Migraine, anxiety, and depression are comorbid and share common genetic traits.[3]

 

Migraines are Multifactorial

There are associated gene disturbances in migraine patterns. Identifying the genes associated with these disturbances is key to developing accurate diagnosis and actionable targeted treatment. Migraines vary in intensity and usually cause throbbing pain in one area of the head, often accompanied by nausea, vomiting, and extreme sensitivity to light and sound. These recurrent headaches typically begin in childhood or adolescence and can be triggered by certain foods, emotional stress, and minor head trauma. Each headache may last from a few hours to a few days.

Severe migraine episodes have been reported in some people with familial hemiplegic migraine. These episodes have included fever, seizures, prolonged weakness, coma, and, rarely, death. Although most people with familial hemiplegic migraine recover completely between episodes, neurological symptoms such as memory loss and problems with attention can last for weeks or months. About 20 percent of people with this condition develop mild but permanent difficulty coordinating movements (ataxia), which may worsen with time, and rapid, involuntary eye movements called nystagmus.

 

Common Migraine Symptoms

  • Severe headache (with or without aura)
  • Fatigue
  • Food cravings
  • Thirst
  • Mood changes
  • Neck stiffness
  • Vision issues – blurring, spots, flashes, etc.
  • Light sensitivity
  • Sound sensitivity
  • Temporary loss of hearing
  • Ear pain
  • Sinus pressure
  • Dizziness / vertigo
  • Numbness / tingling / weakness
  • Nausea / vomiting

 

GeneSavvy MigrainePainGS

The GeneSavvy MigrainePainGS Panel is a unique genetic sequencing service that looks at genes associated with disorders that feature migraine pain, including coenzyme Q10 deficiency, mitochondrial DNA depletion syndrome, advanced sleep-phase syndrome, dystonia, and others. The panel also looks at major biochemical pathways and receptors that can play a role.[4][5] The genetic analysis identifies:

  • Exon variants in 250 genes associated with migraine disorders
  • SNP analysis for 1100 common general wellness single genetic locations
  • Genetic data results with references and informational links delivered securely to your healthcare provider 

 

Some Migraine-Related Disorders

  • CoQ-10 deficiency
  • Riboflavin deficiency
  • GLUT1 deficiency
  • Mitochondrial DNA depletion syndrome
  • Advanced sleep-phase syndrome
  • Dystonia
  • Periodic fever
  • Episodic pain syndrome

 

Key Migraine Genes:

ATP1A2, ATP1A3, CACNA1A, CACNA1S, COQ2, COQ4, COQ6, COQ7, COQ8A, CSNK1D, GABBR2, GABRA1, GABRA2, GABRA3, GABRB1, GABRB2, GABRB3, GABRD, GABRE, GABRG2, GABRQ, GRIN1, GRIN2A, GRIN2B, GRIN2C, GRIN2D, GRIN3A, GRIN3B, GRINA, HTR1A, HTR2A, HTR3A, KCNK18, MAGT1, MR1, MTHFR, NOTCH3, PDSS1, PDSS2, POLG, PRRT2, SCN10A, SCN11A, SCN1A, SCN9A, SLC2A1, SLC52A1, SLC6A4, TRAP1

 

Typical Migraine Treatments

Supplements Diet and Specific Treatment

  • CoQ-10 (Coenzyme Q-10)
  • Riboflavin (Vitamin B2)
  • 5-HTP (5-Hydroxytryptophan)
  • Magnesium
  • Feverfew (Tanacetum parthenium)
  • Ginger
  • L-5MTHF (L-Methylfolate)
  • Lifestyle Management
  • Grain and Gluten-free diet
  • Ketogenic diet
  • Low Antigen Diet
  • Biohomeopathic Approaches
  • Cervical and Soft Tissue Corrections
  • Group IV Laser Therapy
  • BoTox Injections
  • Caffeine, alcohol, and MSG avoidance
  • Trigger identification and avoidance

Acute Medications

  • Analgesics / NSAIDs
  • Anti-migraine medications
  • Anti-nausea medications

Preventative Medications

  • Beta-blockers
  • Anti-serotonergic medications (SSRIs)
  • Tricyclic antidepressants (TCAs)
  • Anti-convulsants (AEDs)
  • Calcium channel blockers

 

Conclusion

Identifying key gene / variants associated with chronic pain and migraine patterns is an extremely valuable clinical / diagnostic / actionable treatment analysis. Utilizing genetic testing along with identifying environmental influences upon gene sensitivity and susceptibility is a vital first step in identifying initiating factors in chronic pain and migraine patterns. [6]

 

 

 

 

 

[1] https://www.ncbi.nlm.nih.gov/pubmed/15613211

[2] https://www.ncbi.nlm.nih.gov/pubmed/8522335

[3] https://www.ncbi.nlm.nih.gov/pubmed/8366469

[4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763681/

[5] https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-016-0346-4

[6] https://thejournalofheadacheandpain.springeropen.com/track/pdf/10.1186/s10194-017-0729-y?site=thejournalofheadacheandpain.springeropen.com

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.

 

 

References

Yuskaitis CJ, Mines MA, King MK, Sweatt JD, Miller CA, Jope RS: Lithium ameliorates altered glycogen synthase kinase-3 and behavior in a mouse model of fragile X syndrome. Biochem Pharmacol. 2010, 79 (4): 632-46. 10.1016/j.bcp.2009.09.023.Google Scholar

Yorbik O, Akay C, Sayal A, Cansever A, Sohmen T, Cavdar AO: Zinc Status in Autistic Children. J Trace Elements Experimental Medicine. 2004, 17: 101-107. 10.1002/jtra.20002.Google Scholar

Yap IK, Angley M, Veselkov KA, Holmes E, Lindon JC, Nicholson JK: Urinary Metabolic Phenotyping Differentiates Children with Autism from Their Unaffected Siblings and Age-Matched Controls. J Proteome Res. 2010, 9 (6): 2996-3004. 10.1021/pr901188e.Google Scholar

Xia W, Zhou Y, Sun C, Wang J, Wu L: A preliminary study on nutritional status and intake in Chinese children with autism. Eur J Pediatr. 2010, 69 (10): 1201-6.Google Scholar

Wyatt DT, Nelson D, Hillman RE: Age-dependent changes in thiamin concentrations in whole blood and cerebrospinal fluid in infants and children. Am J Clin Nutr. 1991, 53 (2): 530-6.Google Scholar

World Health Organization: Assessment of iodine deficiency disorders and monitoring their elimination: a guide for programme managers. 2007, World Health Organization: Geneva (Switzerland), accessed May 2011, [http://whqlibdoc.who.int/publications/2007/9789241595827_eng.pdf]3Google Scholar

Weissman JR, Kelley RI, Bauman ML, Cohen BH, Murray KF, Mitchell RL, Kern RL, Natowicz MR: Mitochondrial disease in autism spectrum disorder patients: a cohort analysis. PLoS One. 2008, 3 (11): e3815-10.1371/journal.pone.0003815.Google Scholar

Waring RH, Ngong JM, Klovsra L, Green S, Sharp H: Biochemical Parameters in Autistic Children. Dev Brain Dysfunct. 1997, 10: 40-43.Google Scholar

Waring RH, Klovrsa LV: Sulfur Metabolism in Autism. J Nutritional & Environmental Medicine. 2000, 10: 25-32. 10.1080/13590840050000861.Google Scholar

Vogeser M, Kyriatsoulis A, Huber E, Kobold U: Candidate reference method for the quantification of circulating 25-hydroxyvitamin D3 by liquid chromatography-tandem mass spectrometry. Clin Chem. 2004, 50 (8): 1415-7. 10.1373/clinchem.2004.031831.Google Scholar

Van Oudheusden LJ, Scholte HR: Efficacy of carnitine in the treatment of children with attention-deficit hyperactivity disorder. Prostaglandins, Leukotrienes and Essential Fatty Acids. 2002, 67 (1): 33-38. 10.1054/plef.2002.0378.Google Scholar

Van Haard PM, Engel R, Pietersma-de Bruyn AL: Quantitation of trans-vitamin K1 in small serum samples by off-line multidimensional liquid chromatography. Clin Chim Acta. 1986, 157 (3): 221-30. 10.1016/0009-8981(86)90297-4.Google Scholar

U.S Centers for Disease Control and Prevention: National Report on Biochemical Indicators of Diet and Nutrition in the U.S. Population 1999-2002. 2008, Atlanta (GA): National Center for Environmental HealthGoogle Scholar

Thurnham DI: Micronutrients and immune function: some recent developments. J Clin Pathol. 1997, 50: 887-91. 10.1136/jcp.50.11.887.Google Scholar

Tabor H, Wyngarden LA: Method for the Determination of Formiminoglutamic Acid in Urine. J Clin Invest. 1958, 37: 824-828. 10.1172/JCI103670.Google Scholar

Stevens RD, Hillman SL, Worthy S, Sanders D, Millington DS: Assay for free and total carnitine in human plasma using tandem mass spectrometry. Clin Chem. 2000, 46 (5): 727-9.Google Scholar

Stabler SP, Allen RH: Quantification of Serum and Urinary S-Adenosylmethionine and S-Adenosylhomocysteine by Stable-Isotope-Dilution Liquid Chromatography-Mass Spectrometry. Clinical Chemistry. 2004, 50: 365-372. 10.1373/clinchem.2003.026252.Google Scholar

Sohler A, Holsztyimska E, Pfeiffer CC: A Rapid Screening Test for Pyroluria; Useful in Distinguishing a Schizophrenic Subpopulation. Orthomolecular Psych. 1978, 3: 273-279.Google Scholar

Sobotka H, Baker H, Ziffer H: Distribution of vitamin B12 between plasma and cells. Am J Clin Nutr. 1960, 8: 283-4.Google Scholar

Serajee FJ, Nabi R, Zhong H, Mahbubul Huq AH: Association of INPP1, PIK3CG, and TSC2 gene variants with autistic disorder: implications for phosphatidylinositol signalling in autism. J Med Genet. 2003, 40 (11): e119-10.1136/jmg.40.11.e119.Google Scholar

Selvaraj RJ, Susheela TP: Estimation of serum vitamin A by a microfluorometric procedure. Clin Chim Acta. 1970, 27 (1): 165-70. 10.1016/0009-8981(70)90391-8.Google Scholar

Schrauzer GN, Shrestha KP: Lithium in drinking water and the incidences of crimes, suicides, and arrests related to drug addictions. Biol Trace El. Res. 1990, 25: 105-113. 10.1007/BF02990271.Google Scholar

Schoenthaler SJ, Bier ID: The effect of vitamin-mineral supplementation on the intelligence of American schoolchildren: a randomized, double-blind placebo-controlled trial. J of Altern and Comple Med. 2000, 6 (1): 19-29. 10.1089/acm.2000.6.19.Google Scholar

Schleicher RL, Carroll MD, Ford ES, Lacher DA: Serum vitamin C and the prevalence of vitamin C deficiency in the United States: 2003-2004 National Health and Nutrition Examination Survey (NHANES). Am J Clin Nutr. 2009, 90 (5): 1252-63. 10.3945/ajcn.2008.27016.Google Scholar

Rolf LH, Haarmann FY, Grotemeyer KH, Kehrer H: Serotonin and amino acid content in platelets of autistic children. Acta Psychiatr Scand. 1993, 87 (5): 312-6. 10.1111/j.1600-0447.1993.tb03378.x.Google Scholar

Rimland B, Edelson S: Autism Treatment Evaluation Checklist: Statistical Analyses. Autism Research Institute. 2000Google Scholar

Quaife ML, Scrimshaw NS, Lowry OH: A micromethod for assay of total tocopherols in blood serum. J Biol Chem. 1949, 180 (3): 1229-35.Google Scholar

Puchyr RF, Bass DA, Gajewski R, Calvin M, Marquardt W, Urek K, Druyan ME, Quig D: Preparation of hair for measurement of elements by inductively coupled plasma-mass spectrometry (ICP-MS). Biol Trace Elem Res. 1998, 62 (3): 167-82. 10.1007/BF02783969.Google Scholar

Pronsky ZM, Crowe JP, Elbe D: Food Medication Interactions. 2008, Birchrunville PA, 15Google Scholar

Pebay-Peyroula E, Dahout-Gonzalez C, Kahn R, Trézéguet V, Lauquin GJ, Brandolin G: Structure of mitochondrial ADP/ATP carrier in complex with carboxyatractyloside. Nature. Nature. 2003, 426: 39-44. 10.1038/nature02056.Google Scholar

Pearson WN: Biochemical appraisal of nutritional status in man. Am J Clin Nutr. 1962, 11: 462-76.Google Scholar

Paşca SP, Dronca E, Kaucsár T, Cřaciun EC, Endreffy E, Ferencz BK, Iftene F, Benga I, Cornean R, Banerjee R, Dronca M: One carbon metabolism disturbances and the C677T MTHFR gene polymorphism in children with autism spectrum disorders. J Cell Mol Med. 2009, 13 (10): 4229-4238. 10.1111/j.1582-4934.2008.00463.x.Google Scholar

Pangborn J: Detection of Metabolic Disorders in People with Autism. Proceedings of the 1984 Annual Conference of the National Society for Children and Adults with Autism. 1984, San Antonio, Texas, 32-51.Google Scholar

Ornoy A: Valproic acid in pregnancy: How much are we endangering the embryo and fetus?. Reproductive Toxicology. 2009, 28: 1-10. 10.1016/j.reprotox.2009.02.014.Google Scholar

Oliveira G, Diogo L, Grazina M, Garcia P, Ataíde A, Marques C, Miguel T, Borges L, Vicente AM, Oliveira CR: Mitochondrial dysfunction in autism spectrum disorders: a population-based study. Dev Med Child Neurol. 2005, 47 (3): 185-9. 10.1017/S0012162205000332.Google Scholar

Oliveira G, Ataíde A, Marques C, Miguel TS, Coutinho AM, Mota-Vieira L, Gonçalves E, Lopes NM, Rodrigues V, Carmona da Mota H, Vicente AM: Epidemiology of autism spectrum disorder in Portugal: prevalence, clinical characterization, and medical conditions. Dev Med Child Neurol. 2007, 49 (10): 726-33. 10.1111/j.1469-8749.2007.00726.x.Google Scholar

Okamoto T, Fukunaga Y, Ida Y, Kishi T: Determination of reduced and total ubiquinones in biological materials by liquid chromatography with electrochemical detection. J Chromatogr. 1988, 430 (1): 11-9.Google Scholar

O’Reilly BA, Warning RH: Enzyme and Sulphur Oxidation Deficiencies in Autistic Children with Known Food/Chemical Sensitivities. J Orthomolecular Medicine. 1993, 8 (4): 198-200.Google Scholar

Nogovitsina OR, Levitina EV: Diagnostic value of examination of the magnesium homeostasis in children with attention deficit syndrome with hyperactivity. Klinicheskaia Laboratornaia Diagnostika. 2005, 5: 17-19.Google Scholar

Mousain-Bosc M, Roche M, Rapin J, Bali J-P: Magnesium vit B6 intake reduces central nervous system hyperexcitability in children. J American College of Nutrition. 2004, 23 (5): 545S-548S.Google Scholar

Morena-Fuenmayor J, Borjas I, Arrieta A, Balera V, Socorro-Candanoza I: Plasma excitatory amino acids in autism. Investigacion Clinica. 1996, 37: 113-128.Google Scholar

Molloy CA, Kalkwarf HJ, Manning-Courtney P, Mills JL, Hediger ML: Plasma 25(OH)D concentration in children with autism spectrum disorder. Dev Med Child Neurol. 2010, 52 (10): 969-71. 10.1111/j.1469-8749.2010.03704.x. Epub 2010 May 24Google Scholar

Ming X, Brimacombe M, Wagner GC: Prevalence of motor impairment in autism spectrum disorders. Brain Dev. 2007, 29 (9): 565-70. 10.1016/j.braindev.2007.03.002.Google Scholar

Miller RC, Brindle E, Holman DJ, Shofer J, Klein NA, Soules MR, O’Connor KA: Comparison of specific gravity and creatinine for normalizing urinary reproductive hormone concentrations. Clin Chem. 2004, 50 (5): 924-32. 10.1373/clinchem.2004.032292.Google Scholar

Miller RC, Brindle E, Holman DJ, Shofer J, Klein NA, Soules MR, O’Connor KA: Comparison of specific gravity and creatinine for normalizing urinary reproductive hormone concentrations. Clin Chem. 2004, 50 (5): 924-32. 10.1373/clinchem.2004.032292.Google Scholar

Michelet F, Gueguen R, Leroy P, Wellman M, Nicolas A, Siest G: Blood and plasma glutathione measured in healthy subjects by HPLC: relation to sex, aging, biological variables, and life habits. Clin Chem. 1995, 41 (10): 1509-17.Google Scholar

Melnyk S, Pogribna M, Pogribny IP, Yi P, James SJ: Measurement of plasma and intracellular S-adenosylmethionine and S-adenosylhomocysteine utilizing coulometric electrochemical detection: alterations with plasma homocysteine and pyridoxal 5′-phosphate concentrations. Clin Chem. 2000, 46 (2): 265-72.Google Scholar

Mehl-Madrona L, Leung B, Kennedy C, Paul S, Kaplan BJ: Micronutrients versus standard medication management in autism: a naturalistic case-control study. J Child Adolesc Psychopharmacol. 2010, 20 (2): 95-103. 10.1089/cap.2009.0011.Google Scholar

Meguid NA, Hashish AF, Anwar M, Sidhom G: Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010, 16 (6): 641-5. 10.1089/acm.2009.0349.Google Scholar

McGinnis WR, Audhya T, Walsh WJ, Jackson JA, McLaren-Howard J, Lewis A, Lauda PH, Bibus DM, Jurnak F, Lietha R, Hoffer A: Discerning the Mauve Factor, Part 1. Altern Ther Health Med. 2008, 14 (2): 40-50.Google Scholar

McDougle CJ, Naylor ST, Cohen DJ, Aghajanian GK, Heninger GR, Price LH: Effects of tryptophan depletion in drug-free adults with autistic disorder. Arch Gen Psychiarty. 1996, 53 (11): 993-1000.Google Scholar

Magera MJ, Helgeson JK, Matern D, Rinaldo P: Methylmalonic acid measured in plasma and urine by stable-isotope dilution and electrospray tandem mass spectrometry. Clin Chem. 2000, 46 (11): 1804-10.Google Scholar

Lepage N, McDonald N, Dallaire L, Lambert M: Age-specific distribution of plasma amino acid concentrations in a healthy pediatric population. Clin Chem. 1997, 43 (12): 2397-402.Google Scholar

Latif A, Heinz P, Cook R: Iron Deficiency in Autism and Asperger Syndrome. Autism. 2002, 6: 103-10.1177/1362361302006001008.Google Scholar

Krajkovicova-Kudlackova M, Valachovicova M, Mislanova C, Hudecova Z, Sudstrova M, Ostatnikova D: Plasma concentration of selected antioxidants in autistic children and adolescents. Bratisl Lek Listy. 2009, 110 (4): 247-250.Google Scholar

Konstantareas MM, Homatidis S: Ear infections in autistic and normal children. J Autism Dev Disord. 1987, 17: 585-594. 10.1007/BF01486973.Google Scholar

Kloor D, Osswald H: S-adenosylhomocysteine hydrolase as a target for intracellular adenosine action. Trends Pharmacol Sci. 2004, 25: 294-7. 10.1016/j.tips.2004.04.004.Google Scholar

Kloor D, Lüdtke A, Stoeva S, Osswald H: Adenosine binding sites at S-adenosylhomocysteine hydrolase are controlled by the NAD+/NADH ratio of the enzyme. Biochem Pharmacol. 2003, 66: 2117-23. 10.1016/S0006-2952(03)00581-1.Google Scholar

Klemm A, Klemm A, Steiner T, Flötgen U, Cumme GA, Horn A: Determination, purification, and characterization of alpha-NADH and alpha-NADPH. Methods Enzymol. 1997, 280: 171-86.Google Scholar

Jory J, McGinnis W: Red-Cell Trace Minerals in Children with Autism. American Journal of Biochemistry and Biotechnology. 2008, 4 (2): 101-104.Google Scholar

James SJ, Melnyk S, Jernigan S, Cleves MA, Halsted CH, Wong DH, Cutler P, Bock K, Boris M, Bradstreet JJ, Baker SM, Gaylor DW: Metabolic endophenotype and related genotypes are associated with oxidative stress in children with autism. Am J Med Genet B Neuropsychiatr Genet. 2006, 141: 947-956.Google Scholar

James SJ, Melnyk S, Fuchs G, Reid T, Jernigan S, Pavliv O, Hubanks A, Gaylor DW: Efficacy of methylcobalamin and folinic acid treatment on glutathione redox status in children with autism. Am J Clin Nutr. 2009, 89 (1): 425-30.Google Scholar

James SJ, Cutler P, Melnyk S, Jernigan S, Janak L, Gaylor DW, Neubrander JA: Metabolic biomarkers of increased oxidative stress and impaired methylation capacity in children with autism. Am J Clin Nutr. 2004, 80 (6): 1611-7.Google Scholar

Jackson MJ, Gerard PJ: Plasma Zinc, Copper, and Amino Acid Levels in the Blood of Autistic Children. J Autism Childhood Schizophrenia. 1978, 8 (2): 203-208. 10.1007/BF01537869.Google Scholar

Horvath K, Perman JA: Autistic disorder and gastrointestinal disease. Curr Opin Pediatr. 2002, 14: 583-587. 10.1097/00008480-200210000-00004.Google Scholar

Herbert V, Baker H, Frank O, Pasher I, Sobotka H, Wasserman LR: The measurement of folic acid activity in serum: a diagnostic aid in the differentiation of the megaloblastic anemias. Blood. 1960, 15: 228-35.Google Scholar

Harmsen E, de Jong JW, Serruys PW: Hypoxanthine production by ischemic heart demonstrated by high pressure liquid chromatography of blood purine nucleosides and oxypurines. Clin Chim Acta. 1981, 115 (1): 73-84. 10.1016/0009-8981(81)90108-X.Google Scholar

Harding KL, Judah RD, Gant CE: Outcome-based comparison of Ritalin versus food-supplement treated children with AD/HD. Alternative Medicine Review. 2003, 8 (3): 319-330.Google Scholar

Harden CL, Pennell PB, Koppel BS, Hovinga CA, Gidal B, Meador KJ, Hopp J, Ting TY, Hauser WA, Thurman D, Kaplan PW, Robinson JN, French JA, Wiebe S, Wilner AN, Vazquez B, Holmes L, Krumholz A, Finnell R, Shafer PO, Le Guen C: Practice Parameter Update: Management issues for women with epilepsy–focus on pregnancy (an evidence-based review): Vitamin K, folic acid, blood levels, and breastfeeding. Neurology. 2009, 73 (2): 126-132. 10.1212/WNL.0b013e3181a6b2f8.Google Scholar

Gorman MW, Feigl EO, Buffington CW: Human plasma ATP concentration. Clin Chem. 2007, 53 (2): 318-25.Google Scholar

Gökçe S, Durmaz Ö, Çeltik C, Aydoğan A, Güllüoğlu M, Sökücü S: Valproic Acid–Associated Vanishing Bile Duct Syndrome. Journal of Child Neurology. 2010, 25 (7): 909-911. 10.1177/0883073809343474.Google Scholar

Geier DA, Kern JK, Garver CR, Adams JB, Audhya T, Geier MR: A prospective study of transsulfuration biomarkers in autistic disorders. Neurochem Res. 2009, 34 (2): 386-93. 10.1007/s11064-008-9782-x. Erratum in: Neurochem Res. 2009, 34(2):394Google Scholar

Faber S, Zinn GM, Kern JC, Kingston HM: The plasma zinc/serum copper ratio as a biomarker in children with autism spectrum disorders. Biomarkers. 2009, 14 (3): 171-180. 10.1080/13547500902783747.Google Scholar

El-Ansary A, Al-Daihan S, Al-Dbass A, Al-Ayadhi L: Measurements of selected ions related to oxidative stress and energy metabolism in Saudi autistic children. Clin Biochem. 2010, 43 (1-2): 63-70. 10.1016/j.clinbiochem.2009.09.008.Google Scholar

Dosman CF, Drmic IE, Brian JA, Senthilselvan A, Harford M, Smith R, Roberts SW: Ferritin as an indicator of suspected iron deficiency in children with autism spectrum disorder: prevalence of low serum ferritin concentration. Dev Med Child Neurol. 2006, 48 (12): 1008-9. 10.1017/S0012162206232225.Google Scholar

Creeke PI, Seal AJ: Quantitation of the niacin metabolites 1-methylnicotinamide and l-methyl-2-pyridone-5-carboxamide in random spot urine samples, by ion-pairing reverse-phase HPLC with UV detection, and the implications for the use of spot urine samples in the assessment of niacin status. J Chromatogr B Analyt Technol Biomed Life Sci. 2005, 817 (2): 247-53. 10.1016/j.jchromb.2004.12.012.Google Scholar

Correia C, Coutinho AM, Diogo L, Grazina M, Marques C, Miguel T, Ataíde A, Almeida J, Borges L, Oliveira C, Oliveira G, Vicente AM: Brief report: High frequency of biochemical markers for mitochondrial dysfunction in autism: no association with the mitochondrial aspartate/glutamate carrier SLC25A12 gene. J Autism Dev Disord. 2006, 36 (8): 1137-40. 10.1007/s10803-006-0138-6.Google Scholar

Cohen IL, Schmidt-Lackner S, Romanczyk R, Sudhalter V: The PDD Behavior Inventory: a rating scale for assessing response to intervention in children with pervasive developmental disorder. J Autism Dev Disord. 2003, 33 (1): 31-45. 10.1023/A:1022226403878.Google Scholar

Chauhan A, Chauhan V: Oxidative stress in autism. Pathophysiology. 2006, 13 (3): 171-81. 10.1016/j.pathophys.2006.05.007.Google Scholar

Chauhan A, Chauhan V, Brown WT, Cohen IL: Oxidative stress in autism: Increased lipid peroxidation and reduced serum levels of ceruloplasmin and transferrin – the antioxidant proteins. Life Sci. 2004, 75: 2539-2549. 10.1016/j.lfs.2004.04.038.Google Scholar

Chattaraj S, Das AK: Indirect atomic absorption spectrometric determination of sulfate in human blood serum. Analyst. 1992, 117 (3): 413-6. 10.1039/an9921700413.Google Scholar

Carlton RM, Ente G, Blum L, Heyman N, Davis W, Ambrosino S: Rational dosages of nutrients have a prolonged effect on learning disabilities. Alt Therapies. 2000, 6 (3): 85-91.Google Scholar

Cannell JJ: Autism and vitamin D. Med Hypothesis. 2008, 70 (4): 750-9. 10.1016/j.mehy.2007.08.016.Google Scholar

Burtis CA, Ashwood ER: Tietz Textbook of Clinical Chemistry. 1999, Philadelphia: W.B. Saunders Company, 3Google Scholar

Breakey J: The role of diet and behavior in childhood. J Paediatr Child Health. 1997, 33: 190-194. 10.1111/j.1440-1754.1997.tb01578.x.Google Scholar

Bertoli S, Cardinali S, Veggiotti P, Trentani C, Testolin G, Tagliabue A: Evaluation of nutritional status in children with refreactory epilepsy. Nutrition Journal. 2006, 5: 14-10.1186/1475-2891-5-14.Google Scholar

Belenky P, Bogan KL, Brenner C: NAD+ metabolism in health and disease. Trends Biochem Sci. 2007, 32 (1): 12-9. 10.1016/j.tibs.2006.11.006. Erratum in: Trends Biochem Sci. 2008, 33(1):1Google Scholar

Baker H, Frank O, Tuma DJ, Barak AJ, Sorrell MF, Hutner SH: Assay for free and total choline activity in biological fluids and tissues of rats and man with Torulopsis pintolopessi. Am J Clin Nutr. 1978, 31 (3): 532-40.Google Scholar

Baker H, Frank O, Pasher I, Hutner SH, Sobotka H: Nicotinic acid assay in blood and urine. Clin Chem. 1960, 6: 572-7.Google Scholar

Baker H, Frank O, Pasher I, Dinnerstein A, Sobotka H: An assay for pantothenic acid in biologic fluids. Clin Chem. 1960, 6: 36-42.Google Scholar

Baker H, Frank O, Ning M, Gellene RA, Hutner SH, Leevy CM: A protozoological method for detecting clinical vitamin B6 deficiency. Am J Clin Nutr. 1966, 18 (2): 123-33.Google Scholar

Baker H, Frank O, Matovitch VB, Pasher I, Aaronson S, Hutner SH, Sobotka H: A new assay method for biotin in blood, serum, urine, and tissues. Anal Biochem. 1962, 3: 31-9. 10.1016/0003-2697(62)90041-6.Google Scholar

Baker H, Frank O, Fennelly JJ, Leevy CM: A Method for Assaying Thiamine Status in Man and Animals. Am J Clin Nutr. 1964, 14: 197-201.Google Scholar

Baker H, Frank O, Feingold S, Gellene RA, Leevy CM, Hutner SH: A riboflavin assay suitable for clinical use and nutritional surveys. Am J Clin Nutr. 1966, 19 (1): 17-26.Google Scholar

Baker H, Deangelis B, Baker ER, Hutner SH: A practical assay of lipoate in biologic fluids and liver in Health and disease. Free Radic Biol Med. 1998, 25 (4-5): 473-9. 10.1016/S0891-5849(98)00087-2.Google Scholar

Arnold GL, Hyman SL, Mooney RA, Kirby RS: Plasma amino acids profiles in children with autism: potential risk of nutritional deficiencies. J Autism Dev Disord. 2003, 33 (4): 449-54. 10.1023/A:1025071014191.Google Scholar

Anke M, Arhnold W, Groppel B, Krause U: The Biological Importance of Lithium. Lithium in Biology and Medicine. Edited by: Schrauzer GN, Klippel, KF. 1991, Weinheim: VCH Verlag, 149-167.Google Scholar

Aldred S, Moore KM, Fitzgerald M, Waring RH: Plasma amino acid levels in children with autism and their families. J Autism Dev Disord. 2003, 33 (1): 93-7. 10.1023/A:1022238706604.Google Scholar

Alberti A, Pirrone P, Elia M, Waring RH, Romano C, Alberti A, Pirrone P, Elia M, Waring RH, Romano C: Sulphation deficit in “low-functioning” autistic children: a pilot study. Biol Psychiatry. 1999, 46 (3): 420-4. 10.1016/S0006-3223(98)00337-0.Google Scholar

Al-Gadani Y, El-Ansary A, Attas O, Al-Ayadhi L: Metabolic biomarkers related to oxidative stress and antioxidant status in Saudi autistic children. Clin Biochem. 2009, 42 (10-11): 1032-40. 10.1016/j.clinbiochem.2009.03.011.Google Scholar

Ahmed N, Thornalley PJ: Quantitative screening of protein biomarkers of early glycation, advanced glycation, oxidation and nitrosation in cellular and extracellular proteins by tandem mass spectrometry multiple reaction monitoring. Biochemical Society Transactions. 2003, 31: 1417-1422. 10.1042/BST0311417.Google Scholar

Adams M, Lucock M, Stuart J, Fardell S, Baker K, Ng X: Preliminary evidence for involvement of the folate gene polymorphism 19 bp deletion-DHFR in occurrence of autism. Neurosci Lett. 2007, 422 (1): 24-9. 10.1016/j.neulet.2007.05.025.Google Scholar

Adams JB, Romdalvik J, Ramanujam VMS, Legator MS: Mercury, lead, and zinc in baby teeth of children with autism vs. controls. J. Toxicology Environ. Health A. 2007, 70: 1046-1051. 10.1080/15287390601172080.Google Scholar

Adams JB, Romdalvik J, Levine KE, Hu L-W: Mercury in First-Cut Baby Hair of Children with Autism vs. Typically-Developing Children. Toxicological and Environmental Chemistry. 2008, 90 (4): 739-753. 10.1080/02772240701699294.Google Scholar

Adams JB, Holloway CJ: Pilot study of a moderate dose multivitamin/mineral supplement for children with autistic spectrum disorder. Altern Complement Med. 2004, 10 (6): 1033-9. 10.1089/acm.2004.10.1033.Google Scholar

Adams JB, Holloway CE, George F, Quig D: Analyses of toxic metals and essential minerals in the hair of Arizona children with autism and associated conditions, and their mothers. Biol Trace Elem Res. 2006, 110 (3): 193-209. 10.1385/BTER:110:3:193.Google Scholar

Adams JB, Holloway CE, George F, Quig D: Analyses of toxic metals and essential minerals in the hair of Arizona children with autism and associated conditions, and their mothers. Biol Trace Elem Res. 2006, 10 (3): 193-209.Google Scholar

Adams JB, Holloway C: Pilot study of a moderate dose multivitamin/mineral supplement for children with autistic spectrum disorder. J Altern Complement Med. 2004, 10 (6): 1033-9. 10.1089/acm.2004.10.1033.Google Scholar

Adams JB, George F, Audhya T: Abnormally high plasma levels of vitamin B6 in children with autism not taking supplements compared to controls not taking supplements. J Altern Complement Med. 2006, 12 (1): 59-63. 10.1089/acm.2006.12.59.Google Scholar

Adams JB, George F, Audhya T: Abnormally high plasma levels of vitamin B6 in children with autism not taking supplements compared to controls not taking supplements. J Altern Complement Med. 2006, 12 (1): 59-63. 10.1089/acm.2006.12.59.Google Scholar

Adams JB, Baral M, Geis E, Mitchell J, Ingram J, Hensley A, Zappia I, Newmark S, Gehn E, Rubin RA, Mitchell K, Bradstreet J, El-Dahr JM: The severity of autism is associated with toxic metal body burden and red blood cell glutathione levels. J Toxicol. 2009, 2009: 532640-Google Scholar

 

 

 

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

August 16, 2017

GeneSavvy Press Release

For Immediate Release: 7/26/17

 

GeneSavvy Announces Launch in Emerging Wellness as a Service (WaaS) Industry

 

Former Courtagen Employees to Team Up with GeneSavvy

 

 

GeneSavvy, a division of HealthSavvy, Inc. based in Kenmore, WA announces their launch into the emerging Wellness as a Service industry with genome-centric biotechnology built to promote vibrant health through their proprietary decision management software. GeneSavvy Co-Founder and CEO Kris Fobes has been developing GeneSavvy’s intelligent clinical decision platform since 2012 with the launch of subsidiary company, HealthCoach7. HealthCoach7 is a genetic health company focused on developing and providing diagnostics and treatments for children with ASD, developmental delay, and other complex pediatric and adult disorders with successful treatment outcomes worldwide.

 

After hosting the Hyper Wellbeing Summit, Hyper Wellbeing Founder Lee Dryburgh coined the Wellness as a Service (WaaS) model as a way to describe the future of healthcare technology using big data and new technology to empower people to live longer, healthier lives through disease prevention rather than illness reaction. GeneSavvy has been developed over the last 5 years to do exactly that. GeneSavvy leverages biodata to make predictive suggestions that will be scientifically proven to prevent disease, prolong vibrant life, and assist clinical decisions in complex disease cases.

 

Several former Courtagen employees have teamed up with GeneSavvy including former Chief Medical Officer and Genetic Researcher, Dr. Richard G. Boles after Courtagen Life Sciences announced the closure of their medical genetic company on July 18th 2017. Courtagen shut down their medical genetic company to pursue research in genomic cannabis through their subsidiary company, Medicinal Genomics Corporation. The closure of Courtagen has left thousands of doctors and even more families in need of a company that can offer similar services. With GeneSavvy’s technology and a few of Courtagen’s former brilliant minds, GeneSavvy is well positioned to fill that void and provide the services those medical professionals and families need.

 

GeneSavvy will be accepting genetic testing orders starting in August 2017 through our websites www.GeneSavvy.com. Our genetic testing panels will be sequenced using Illumina’s Next Generation Sequencing Technology and processed through GeneSavvy’s proprietary bioinformatics pipeline and report software. Our proprietary bioinformatics pipeline and reporting software will be built in collaboration with several pioneers in Functional Genetics to be an extremely comprehensive and actionable system for ASD, developmental delay, and other complex pediatric neurological disorders. Actionable genetic reports for chronic regional pain disorders, mitochondrial and metabolic disorders, epilepsy and seizure disorders and other complex disorders will be available soon after.

 

GeneSavvy is currently offering several genetic panels, including the NeuroDevGS panel which is an extremely comprehensive panel to cover genes involved in Autism Spectrum, Developmental Delay, and other Complex Neurological Disorders. Another comprehensive test offered by GeneSavvy is their LongevityGS panel. This panel was built to bring next generation sequencing technology to the genes looked at by some of leaders in functional medicine for holistic health. GeneSavvy also covers Whole Exome genetic testing through their PowerXomeGS panel. If you’re looking for one of the most comprehensive genetic tests available in the market, the PowerXomeGS would be a great place to start. All of GeneSavvy’s genetic tests will be ordered by physicians. If you don’t have a physician for your genetic needs, we can connect you with one to complete your order. 

 

 

 

UPDATE: 8/15/17

**Due to the amount of inquiries and demand we received after announcing our services, we had to get something online quickly to accept orders. Our website is currently up and accepting orders but the website content is far from complete. will be adding and updating content and features to the website over the next few weeks/months/forever… All of our panels will come with our GeneSavvy Guarantee of Action. No matter what panel you order, we will guarantee there will be health action to take. We define health action as current phenotype treatment, future risk assessment and prevention, nutritional support for pathway inefficiencies, or any other action items added to your health protocol because of our panels.

 

 

GeneSavvy will be offering exclusive discounts on genetic testing for previous Courtagen customers and for new customers that are part of our first 1000 orders. Send us an email at [email protected] if your interested in getting discounted genetic tests.

Mitochondria are the energy producers of human cells. The energy currency for the work that is required to power up metabolism by producing the energy-rich molecule adenosine triphosphate (ATP). The ATP is produced in the mitochondria using energy stored in the food that is consumed.

These ATP’s are essential in keeping every step of metabolism in equilibrium which in turn effects every system of the human body including immunity, detoxification, hormones, brain neurotransmitters, etc.

Genetic testing to determine metabolic efficiency in chronic health concerns is essential. Also essential in conditions like OCD, ADHD, ASD (Autism), Fatigue, Immune Related Fatigue, Chronic Infections, etc

Genetic genotyping and phenotyping assist in identifying key characteristics that involve mitochondrial health. Genetic analysis and action can assist in providing answers and remedy for these concerns.

There are hundreds of mitochondria within human cells and it is crucial to protect the mitochondria from age-related stress and oxidative burden in order to prevent functional disease and aging risk. These mitochondria are power generators that are responsible for the cell grid. If they are compromised the functional performance survival of the cell is jeopardized complete loss can result.

Each mitochondria carries its own small circular DNA genome, called mtDNA, the products of which are required for energy production. Because mtDNA has limited repair abilities, normal and mutant versions of mtDNA are often found in the same cell, a condition known as heteroplasmy. Most people start off life with some level of heteroplasmy, and the levels of mutant mtDNA increase throughout life. When a critical threshold level of mutant mtDNA is passed, cells become nonfunctional or die.

When mitochondria mutant mtDNA is critical a process of mitophagy results. The important goal in targeting mitochondria is to prevent it from getting to the point of no return.

It is essential that thorough assessment be made through genetic analysis that specifically assess mtDNA and corresponding gene controls.

Many health conditions are caused by critical mutant mtDNA including neurodegenerative disease, Autism, Autism Spectrum Disorder, Disorders of Autonomic Control, Schizophrenia, Behavioral Disorders like OCD, ADHD, Metabolic and Gating Disturbances, Chronic Immune Functional Related Fatigue, Chronic Pain Syndrome, etc.

GeneSavvy testing is the best form of analysis for these disorders and should be the first place in working up the foundational causes and needed targeting to address the functional disturbances caused by mutant mtDNA and nuclear mitochondrial gene disturbances.

We have analyzed over 2000 genetic results and can affirm that foundational genetic analysis will dramatically inflence treatment targeting and outcomes.

 

http://www.sciencedirect.com/science/article/pii/S0005272815001097

August 8, 2017

Autism and Connectivity

New gene discoveries that code for neuronal connectivity are beginning to give new hope in targeting therapy to address the problems associated with connectivity. The autism spectrum brain exhibits connectivity disturbances that alters communication between neuronal regions. Neuronal mitochondrial depletion is among the causative factors that create impaired connectivity and synaptic control. There are many genes implicated in this phenomenon.

Genes Studied In ASD

http://www.genecards.org/Search/Keyword…

Research Article Links

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691066/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3420970/

Autism symptoms can be aggravated by inflammatory activity, chronic sensitivity and neurotransmitter trafficking. There are a variety of combination of therapeutically effective agents in personalized treatment.

Some Guidelines

1. Disodium cromoglycate (Gastrocrom)
‘Mast cell stabilizer’ 100 – 400 mg/day dissolved in water

2. Cyproheptadine (Periactin) Serotonin and histamine-1receptor antagonist
1 – 4 mg/day

3. Ketotifen (Zaditen) Histamine-1receptor antagonist, anti-eosinophil 1 – 4 mg/day

4. Rupatadine (Rupafin) Histamine-1 receptor and platelet activating factor antagonist; mast cell inhibitor, anti-eosinophil 20 mg/day

5. NeuroProtek Contains flavonoids and a proteoglycan Two capsules/20 kg body weight/day and Nrf2 as additional item

6. Black Seed Oil 1 tsp 2x day
7. Autoimmune Paleo Dietary Focus
8. Oxytocin Sublingual cycled (Dopamine)
9. SAMe sublingual cycled (Dopamime)
10. CoQ10 mouth spray
11. NAD+ mouth spray
12. Sublingual biotin and folinate
13. Stem cell therapy as option
14. Hyperbaric therapy
15. Immunotherapy
16. Low Dose Naltrexone

*Doses will vary depending on age and weight of patient.

Other Considerations:
1. Carbohydrate (starch splitting) enzyme repletion
2. Human Breast Milk Derived Probiotic Culture
3. Fecal Implantation healthy donor
4. Antimicrobial eradication in complicated cases

Additional Testing Considerations:
1. Folate Receptor Antibody (FRAT)
www.illiadneuro.com
2. Cunningham Panel (PANS / PANDAS)
http://www.moleculeralabs.com/cunningham-panel-pandas-pans…/

Personalized genetics are indeed, personal, powerful, revealing, and relating to an individual’s wellness and longevity. Next generation sequencing and whole exome technology has allowed for the complete capture of the entire human genome.

We have worked with countless numbers of adults and children with complex diseases including autism, neurological development disorders, immunological disorders, metabolic disorders and rare disease with successful cases all over the world. 

Genetic testing is the foundation of discovering more exact diagnostic testing and treatable actions. Tens of thousands of dollars can be saved by discovering the genes and associated pathways before running costly lab testing. Treatment then is more targeted and effective also saving costly dollars in medications and supplements.

GeneSavvy architects this foundation of targeted diagnosis and treatment in a personalized manner through our comprehensive genetic panels and proprietary bioinformatics pipeline.