Unfolded Protein Response and A Possible Treatment for CFS

[mariovitali]

@aquariusgirl

My regimen has much changed from then. As discussed, i am trying to take as less supplements as possible.

It now looks like this :

8:00 : Metafolin, Dibencozide,FMN
9:00 : TMG
10:00 : Alpha-GPC
12:00 TUDCA, P5P, Selenium
16:00 TMG
20:00 Alpha-GPC
24:00 TUDCA


Regarding your question : My hypothesis is that various SNPs work in a kind of a Scoring System which -as you understand- it is a very complicated one.

So the answer is : Supplement with Biotin and evaluate how you feel. I am against in over-supplementing so i would suggest that you do not take more than 100% RDA on any supplement.

 

[Valentijn]

Regarding your question : My hypothesis is that various SNPs work in a kind of a Scoring System which -as you understand- it is a very complicated one.

I regret to inform you that science 100% contradicts your hypothesis. Please try again.

So the answer is : Supplement with Biotin and evaluate how you feel. I am against in over-supplementing so i would suggest that you do not take more than 100% RDA on any supplement.

Why do think that someone with the normal, non-pathogenic, overwhelmingly common version (95% prevalence rate) of a SNP needs to supplement anything for it?

 

[mariovitali]

@Valentijn

OK i know it's too big of a post, but i will make it easier for you :

-CYP7A1
-CYP8B1
-AKR1D1
-Mitochondrial Dysfunction
-Acetylcholine
-Acetyl-CoA
-FXR (Farnesoid X Receptor)
-Bile Acids


PS : Did you see this?


http://www.ncbi.nlm.nih.gov/pubmed/26399744


i know...it doesn't make sense, right?

cutoff=0.1

Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 178 instances (35.39%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[oxalates=T, fxr=T]: 66 ==> [acetyl_coa_carboxylase=T]: 66 <conf1)> lift2.83) lev0.08) conv42.64)
[oxalates=T, akr1d1=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift2.83) lev0.03) conv16.15)
[phospholamban=T, dim=T]: 58 ==> [acetyl_coa_carboxylase=T]: 58 <conf1)> lift2.83) lev0.07) conv37.48)
[phospholamban=T, metronidazole=T]: 42 ==> [acetyl_coa_carboxylase=T]: 42 <conf1)> lift2.83) lev0.05) conv27.14)
[phospholamban=T, sult2a1=T]: 38 ==> [acetyl_coa_carboxylase=T]: 38 <conf1)> lift2.83) lev0.05) conv24.55)
[oxalates=T, propionyl_coa_carboxylase=T]: 64 ==> [acetyl_coa_carboxylase=T]: 63 <conf0.98)> lift2.78) lev0.08) conv20.68)
[acetyl_coa=T, cholangitis=T]: 58 ==> [acetyl_coa_carboxylase=T]: 57 <conf0.98)> lift2.78) lev0.07) conv18.74)
[acetyl_coa=T, isotretinoin=T]: 76 ==> [acetyl_coa_carboxylase=T]: 74 <conf0.97)> lift2.75) lev0.09) conv16.37)
[acetyl_coa=T, methotrexate=T]: 69 ==> [acetyl_coa_carboxylase=T]: 67 <conf0.97)> lift2.74) lev0.08) conv14.86)
[oxalates=T]: 107 ==> [acetyl_coa_carboxylase=T]: 91 <conf0.85)> lift2.4) lev0.11) conv4.07)
[acetyl_coa=T]: 178 ==> [acetyl_coa_carboxylase=T]: 149 <conf0.84)> lift2.37) lev0.17) conv3.83)
[phospholamban=T]: 109 ==> [acetyl_coa_carboxylase=T]: 91 <conf0.83)> lift2.36) lev0.1) conv3.71)




cutoff=0.2
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 121 instances (24.06%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acyl_coa=T, urolithiasis=T, d_limonene=T]: 32 ==> [acetyl_coa_carboxylase=T]: 32 <conf1)> lift4.16) lev0.05) conv24.3)
[acyl_coa=T, urolithiasis=T, testosterone_production=T]: 31 ==> [acetyl_coa_carboxylase=T]: 31 <conf1)> lift4.16) lev0.05) conv23.54)
[acyl_coa=T, urolithiasis=T, three_betahsd=T]: 30 ==> [acetyl_coa_carboxylase=T]: 30 <conf1)> lift4.16) lev0.05) conv22.78)
[acyl_coa=T, fads1=T, testosterone_production=T]: 39 ==> [acetyl_coa_carboxylase=T]: 39 <conf1)> lift4.16) lev0.06) conv29.62)
[acyl_coa=T, human_proteinuria=T, fxr=T]: 35 ==> [acetyl_coa_carboxylase=T]: 35 <conf1)> lift4.16) lev0.05) conv26.58)
[acyl_coa=T, human_proteinuria=T, phospholamban=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift4.16) lev0.05) conv25.06)
[acyl_coa=T, human_proteinuria=T, cyp8b1=T]: 30 ==> [acetyl_coa_carboxylase=T]: 30 <conf1)> lift4.16) lev0.05) conv22.78)
[phospholamban=T, iron_deficiency=T]: 35 ==> [acetyl_coa_carboxylase=T]: 35 <conf1)> lift4.16) lev0.05) conv26.58)
[phospholamban=T, testosterone_production=T]: 55 ==> [acetyl_coa_carboxylase=T]: 54 <conf0.98)> lift4.08) lev0.08) conv20.88)
[pyruvate_carboxylase=T, fxr=T]: 52 ==> [acetyl_coa_carboxylase=T]: 51 <conf0.98)> lift4.08) lev0.08) conv19.75)
[phospholamban=T, liver_regeneration=T]: 50 ==> [acetyl_coa_carboxylase=T]: 49 <conf0.98)> lift4.07) lev0.07) conv18.99)
[acyl_coa=T, fads1=T, car=T]: 45 ==> [acetyl_coa_carboxylase=T]: 44 <conf0.98)> lift4.06) lev0.07) conv17.09)
[pyruvate_carboxylase=T, phospholamban=T]: 44 ==> [acetyl_coa_carboxylase=T]: 43 <conf0.98)> lift4.06) lev0.06) conv16.71)
[acyl_coa=T, fads1=T, propionyl_coa_carboxylase=T]: 43 ==> [acetyl_coa_carboxylase=T]: 42 <conf0.98)> lift4.06) lev0.06) conv16.33)
[pyruvate_carboxylase=T, car=T]: 41 ==> [acetyl_coa_carboxylase=T]: 40 <conf0.98)> lift4.06) lev0.06) conv15.57)
[acyl_coa=T, urolithiasis=T]: 35 ==> [acetyl_coa_carboxylase=T]: 33 <conf0.94)> lift3.92) lev0.05) conv8.86)
[acyl_coa=T, fads1=T]: 55 ==> [acetyl_coa_carboxylase=T]: 51 <conf0.93)> lift3.85) lev0.08) conv8.35)
[acyl_coa=T, human_proteinuria=T]: 41 ==> [acetyl_coa_carboxylase=T]: 38 <conf0.93)> lift3.85) lev0.06) conv7.78)
[pyruvate_carboxylase=T]: 98 ==> [acetyl_coa_carboxylase=T]: 74 <conf0.76)> lift3.14) lev0.1) conv2.98)
[acyl_coa=T]: 113 ==> [acetyl_coa_carboxylase=T]: 84 <conf0.74)> lift3.09) lev0.11) conv2.86)
[phospholamban=T]: 83 ==> [acetyl_coa_carboxylase=T]: 61 <conf0.73)> lift3.06) lev0.08) conv2.74)



cutoff=0.3

Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 95 instances (18.89%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[phosphatidylcholine=T, finasteride=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift5.29) lev0.04) conv21.9)
[phosphatidylcholine=T, lactic_acidosis=T, monosodium_glutamate=T]: 34 ==> [acetyl_coa_carboxylase=T]: 34 <conf1)> lift5.29) lev0.05) conv27.58)
[phosphatidylcholine=T, lactic_acidosis=T, pgc1=T]: 31 ==> [acetyl_coa_carboxylase=T]: 31 <conf1)> lift5.29) lev0.05) conv25.15)
[phosphatidylcholine=T, lactic_acidosis=T, d_aminoacid_oxidase=T]: 30 ==> [acetyl_coa_carboxylase=T]: 30 <conf1)> lift5.29) lev0.05) conv24.33)
[acetyl_coa=T, finasteride=T, gsh=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift5.29) lev0.05) conv26.77)
[acetyl_coa=T, finasteride=T, hepatotoxicity=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift5.29) lev0.05) conv26.77)
[acetyl_coa=T, finasteride=T, hydroxysteroid_dehydrogenase=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift5.29) lev0.05) conv26.77)
[liver_regeneration=T, phospholamban=T]: 40 ==> [acetyl_coa_carboxylase=T]: 39 <conf0.98)> lift5.16) lev0.06) conv16.22)
[liver_regeneration=T, finasteride=T]: 32 ==> [acetyl_coa_carboxylase=T]: 31 <conf0.97)> lift5.13) lev0.05) conv12.98)
[phosphatidylcholine=T, pulmonary_edema=T]: 30 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.97)> lift5.12) lev0.05) conv12.17)
[liver_regeneration=T, five_ht2=T]: 30 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.97)> lift5.12) lev0.05) conv12.17)
[acetyl_coa=T, nafld=T]: 57 ==> [acetyl_coa_carboxylase=T]: 55 <conf0.96)> lift5.11) lev0.09) conv15.41)
[acetyl_coa=T, cholangitis=T]: 27 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.96)> lift5.1) lev0.04) conv10.95)
[phosphatidylcholine=T, lactic_acidosis=T]: 38 ==> [acetyl_coa_carboxylase=T]: 36 <conf0.95)> lift5.02) lev0.06) conv10.27)
[acetyl_coa=T, finasteride=T]: 35 ==> [acetyl_coa_carboxylase=T]: 33 <conf0.94)> lift4.99) lev0.05) conv9.46)
[phosphatidylcholine=T]: 62 ==> [acetyl_coa_carboxylase=T]: 48 <conf0.77)> lift4.1) lev0.07) conv3.35)
[acetyl_coa=T]: 112 ==> [acetyl_coa_carboxylase=T]: 82 <conf0.73)> lift3.88) lev0.12) conv2.93)
[liver_regeneration=T]: 78 ==> [acetyl_coa_carboxylase=T]: 56 <conf0.72)> lift3.8) lev0.08) conv2.75)



cutoff=0.4
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 87 instances (17.3%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acetyl_coa=T, exercise_intolerance=T]: 36 ==> [acetyl_coa_carboxylase=T]: 36 <conf1)> lift5.78) lev0.06) conv29.77)
[acetyl_coa=T, freet3=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift5.78) lev0.05) conv27.29)
[acetyl_coa=T, vitamin_d3=T]: 30 ==> [acetyl_coa_carboxylase=T]: 30 <conf1)> lift5.78) lev0.05) conv24.81)
[phosphatidylcholine=T, three_betahsd=T]: 33 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.97)> lift5.61) lev0.05) conv13.65)
[steatohepatitis=T, phospholamban=T]: 33 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.97)> lift5.61) lev0.05) conv13.65)
[phosphatidylcholine=T, vitamin_k=T]: 31 ==> [acetyl_coa_carboxylase=T]: 30 <conf0.97)> lift5.6) lev0.05) conv12.82)
[steatohepatitis=T, oxalates=T]: 31 ==> [acetyl_coa_carboxylase=T]: 30 <conf0.97)> lift5.6) lev0.05) conv12.82)
[phosphatidylcholine=T, lactic_acidosis=T]: 30 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.97)> lift5.59) lev0.05) conv12.41)
[steatohepatitis=T, insp3=T]: 29 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.97)> lift5.58) lev0.05) conv11.99)
[phosphatidylcholine=T]: 51 ==> [acetyl_coa_carboxylase=T]: 40 <conf0.78)> lift4.53) lev0.06) conv3.51)
[acetyl_coa=T]: 85 ==> [acetyl_coa_carboxylase=T]: 66 <conf0.78)> lift4.49) lev0.1) conv3.51)
[steatohepatitis=T]: 77 ==> [acetyl_coa_carboxylase=T]: 58 <conf0.75)> lift4.35) lev0.09) conv3.18)


cutoff=0.5
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 77 instances (15.31%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acyl_coa=T, testosterone_production=T]: 31 ==> [acetyl_coa_carboxylase=T]: 31 <conf1)> lift6.53) lev0.05) conv26.25)
[acetyl_coa=T, liver_injury=T]: 36 ==> [acetyl_coa_carboxylase=T]: 36 <conf1)> lift6.53) lev0.06) conv30.49)
[acetyl_coa=T, liver_disease=T]: 34 ==> [acetyl_coa_carboxylase=T]: 34 <conf1)> lift6.53) lev0.06) conv28.8)
[acetyl_coa=T, vcam_1=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift6.53) lev0.06) conv27.95)
[glycolysis=T, fxr=T]: 37 ==> [acetyl_coa_carboxylase=T]: 36 <conf0.97)> lift6.36) lev0.06) conv15.67)
[acyl_coa=T, liver_disease=T]: 36 ==> [acetyl_coa_carboxylase=T]: 35 <conf0.97)> lift6.35) lev0.06) conv15.24)
[glycolysis=T, glucocorticoid_receptor=T]: 35 ==> [acetyl_coa_carboxylase=T]: 34 <conf0.97)> lift6.35) lev0.06) conv14.82)
[acyl_coa=T, liver_injury=T]: 35 ==> [acetyl_coa_carboxylase=T]: 34 <conf0.97)> lift6.35) lev0.06) conv14.82)
[glycolysis=T, p450scc=T]: 33 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.97)> lift6.33) lev0.05) conv13.97)
[glycolysis=T]: 60 ==> [acetyl_coa_carboxylase=T]: 48 <conf0.8)> lift5.23) lev0.08) conv3.91)
[acyl_coa=T]: 64 ==> [acetyl_coa_carboxylase=T]: 50 <conf0.78)> lift5.1) lev0.08) conv3.61)
[acetyl_coa=T]: 68 ==> [acetyl_coa_carboxylase=T]: 53 <conf0.78)> lift5.09) lev0.08) conv3.6)



cutoff=0.6
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 69 instances (13.72%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acetyl_coa=T, mitochondrial_dysfunction=T]: 36 ==> [acetyl_coa_carboxylase=T]: 36 <conf1)> lift7.29) lev0.06) conv31.06)
[acetyl_coa=T, liver_injury=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift7.29) lev0.06) conv28.47)
[acetyl_coa=T, catalase=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift7.29) lev0.06) conv28.47)
[glycolysis=T, cyp7a1=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift7.29) lev0.05) conv23.3)
[glycolysis=T, star=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift7.29) lev0.05) conv23.3)
[acyl_coa=T, glycolysis=T, pgc1=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift7.29) lev0.05) conv23.3)
[acyl_coa=T, glycolysis=T, cyp7a1=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift7.29) lev0.04) conv21.57)
[acyl_coa=T, lactic_acidosis=T, acetyl_coa=T]: 29 ==> [acetyl_coa_carboxylase=T]: 29 <conf1)> lift7.29) lev0.05) conv25.02)
[acyl_coa=T, lactic_acidosis=T, pgc1=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift7.29) lev0.04) conv21.57)
[glycolysis=T, endothelial_nos=T]: 32 ==> [acetyl_coa_carboxylase=T]: 31 <conf0.97)> lift7.06) lev0.05) conv13.81)
[acyl_coa=T, fas_ligand=T]: 26 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.96)> lift7.01) lev0.04) conv11.22)
[acyl_coa=T, glycolysis=T]: 34 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.94)> lift6.86) lev0.05) conv9.78)
[acyl_coa=T, lactic_acidosis=T]: 31 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.94)> lift6.82) lev0.05) conv8.92)
[acetyl_coa=T]: 59 ==> [acetyl_coa_carboxylase=T]: 48 <conf0.81)> lift5.93) lev0.08) conv4.24)
[glycolysis=T]: 51 ==> [acetyl_coa_carboxylase=T]: 41 <conf0.8)> lift5.86) lev0.07) conv4)
[acyl_coa=T]: 61 ==> [acetyl_coa_carboxylase=T]: 46 <conf0.75)> lift5.5) lev0.07) conv3.29)


cutoff=0.7
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 60 instances (11.93%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acetyl_coa=T, mitochondrial_dysfunction=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift8.38) lev0.06) conv29.06)
[acetyl_coa=T, oxidative_stress_markers=T]: 33 ==> [acetyl_coa_carboxylase=T]: 33 <conf1)> lift8.38) lev0.06) conv29.06)
[acetyl_coa=T, hmgcoa=T]: 32 ==> [acetyl_coa_carboxylase=T]: 32 <conf1)> lift8.38) lev0.06) conv28.18)
[glucose_6_phosphatase=T, mitochondrial_dysfunction=T, acetyl_coa=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift8.38) lev0.05) conv23.78)
[glucose_6_phosphatase=T, acetyl_coa=T]: 33 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.97)> lift8.13) lev0.06) conv14.53)
[acyl_coa=T, mitochondrial_dysfunction=T]: 30 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.97)> lift8.1) lev0.05) conv13.21)
[acyl_coa=T, ppp=T]: 29 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.97)> lift8.09) lev0.05) conv12.77)
[acyl_coa=T, nox4=T]: 28 ==> [acetyl_coa_carboxylase=T]: 27 <conf0.96)> lift8.08) lev0.05) conv12.33)
[glucose_6_phosphatase=T, atf4=T]: 26 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.96)> lift8.06) lev0.04) conv11.45)
[glucose_6_phosphatase=T, mitochondrial_dysfunction=T]: 31 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.94)> lift7.84) lev0.05) conv9.1)
[acetyl_coa=T]: 56 ==> [acetyl_coa_carboxylase=T]: 44 <conf0.79)> lift6.59) lev0.07) conv3.79)
[acyl_coa=T]: 52 ==> [acetyl_coa_carboxylase=T]: 39 <conf0.75)> lift6.29) lev0.07) conv3.27)
[glucose_6_phosphatase=T]: 48 ==> [acetyl_coa_carboxylase=T]: 36 <conf0.75)> lift6.29) lev0.06) conv3.25)




cutoff=0.8
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 52 instances (10.34%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[glycolysis=T, redox_potential=T, tudca=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift9.67) lev0.05) conv24.21)
[glycolysis=T, redox_potential=T, nox4=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift9.67) lev0.04) conv22.42)
[acetyl_coa=T, hmgcoa=T]: 27 ==> [acetyl_coa_carboxylase=T]: 27 <conf1)> lift9.67) lev0.05) conv24.21)
[glucose_6_phosphatase=T, acetyl_coa=T, tudca=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift9.67) lev0.04) conv22.42)
[glucose_6_phosphatase=T, tudca=T, protein_kinase_c=T]: 25 ==> [acetyl_coa_carboxylase=T]: 25 <conf1)> lift9.67) lev0.04) conv22.42)
[glycolysis=T, tudca=T]: 30 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.97)> lift9.35) lev0.05) conv13.45)
[acetyl_coa=T, mitochondrial_dysfunction=T]: 29 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.97)> lift9.34) lev0.05) conv13)
[glycolysis=T, endothelial_nos=T]: 27 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.96)> lift9.31) lev0.05) conv12.1)
[acetyl_coa=T, bile_acid=T]: 27 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.96)> lift9.31) lev0.05) conv12.1)
[glycolysis=T, redox_potential=T]: 30 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.93)> lift9.03) lev0.05) conv8.97)
[glucose_6_phosphatase=T, acetyl_coa=T]: 29 ==> [acetyl_coa_carboxylase=T]: 27 <conf0.93)> lift9.01) lev0.05) conv8.67)
[glucose_6_phosphatase=T, tudca=T]: 27 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.93)> lift8.96) lev0.04) conv8.07)
[glucose_6_phosphatase=T, mitochondrial_dysfunction=T]: 29 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.9)> lift8.67) lev0.05) conv6.5)
[glycolysis=T]: 41 ==> [acetyl_coa_carboxylase=T]: 32 <conf0.78)> lift7.55) lev0.06) conv3.68)
[acetyl_coa=T]: 47 ==> [acetyl_coa_carboxylase=T]: 36 <conf0.77)> lift7.41) lev0.06) conv3.51)
[glucose_6_phosphatase=T]: 42 ==> [acetyl_coa_carboxylase=T]: 30 <conf0.71)> lift6.91) lev0.05) conv2.9)


cutoff=0.9
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 43 instances (8.55%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acetyl_coa=T, cyp7a1=T]: 26 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.96)> lift11.25) lev0.05) conv11.89)
[steatohepatitis=T, protein_kinase_c=T]: 29 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.86)> lift10.08) lev0.04) conv5.3)
[acetyl_coa=T, acyl_coa=T, baroreceptor=F]: 30 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.83)> lift9.75) lev0.04) conv4.57)
[steatohepatitis=T, mitochondrial_dysfunction=T]: 30 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.83)> lift9.75) lev0.04) conv4.57)
[acyl_coa=T, l_carnitine=T, acetyl_coa=T]: 33 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.79)> lift9.22) lev0.05) conv3.77)
[steatohepatitis=T, l_carnitine=T]: 33 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.79)> lift9.22) lev0.05) conv3.77)
[acetyl_coa=T, acyl_coa=T]: 37 ==> [acetyl_coa_carboxylase=T]: 29 <conf0.78)> lift9.17) lev0.05) conv3.76)
[acetyl_coa=T, l_carnitine=T]: 35 ==> [acetyl_coa_carboxylase=T]: 27 <conf0.77)> lift9.02) lev0.05) conv3.56)
[acyl_coa=T, l_carnitine=T]: 36 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.72)> lift8.45) lev0.05) conv2.99)
[acetyl_coa=T]: 45 ==> [acetyl_coa_carboxylase=T]: 31 <conf0.69)> lift8.06) lev0.05) conv2.74)
[acyl_coa=T]: 44 ==> [acetyl_coa_carboxylase=T]: 30 <conf0.68)> lift7.98) lev0.05) conv2.68)
[steatohepatitis=T]: 51 ==> [acetyl_coa_carboxylase=T]: 30 <conf0.59)> lift6.88) lev0.05) conv2.12)


cutoff=1.0
Hot Spot
========
Total population: 503 instances
Target attribute: acetyl_coa_carboxylase
Target value: T [value count in total population: 40 instances (7.95%)]
Minimum value count for segments: 25 instances (5% of total population)
Maximum branching factor: 3
Maximum rule length: 5
Minimum improvement in target: 5%

[acetyl_coa=T, acyl_coa=T]: 32 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.78)> lift9.82) lev0.04) conv3.68)
[l_carnitine=T, oxidation=T]: 37 ==> [acetyl_coa_carboxylase=T]: 27 <conf0.73)> lift9.18) lev0.05) conv3.1)
[acetyl_coa=T, bradycardia=F]: 36 ==> [acetyl_coa_carboxylase=T]: 25 <conf0.69)> lift8.73) lev0.04) conv2.76)
[acetyl_coa=T]: 43 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.65)> lift8.19) lev0.05) conv2.47)
[acyl_coa=T]: 40 ==> [acetyl_coa_carboxylase=T]: 26 <conf0.65)> lift8.17) lev0.05) conv2.45)
[l_carnitine=T]: 51 ==> [acetyl_coa_carboxylase=T]: 28 <conf0.55)> lift6.9) lev0.05) conv1.96)

 

[Sam7777]

https://www.researchgate.net/public...e_probiotics_bile_acids_axis_and_human_health

 

[Valentijn]

i know...it doesn't make sense, right?

The fact remains that your "hypothesis" requires the complete rejection of everything that is known about genetics, without providing a rational basis for such rejection. You cannot play "count all the SNPs" and presume that the sheer number of them means anything.

To determine if any SNP is relevant, and which genotype is problematic, you absolutely MUST read the research. You cannot guess, you cannot assume. There is no short-cut.

 

[mariovitali]

@Sam7777

 

[aquariusgirl]

So I have fatty liver (ultrasound) zero bilirubin (blood) low secondary bile acids.(CDSA?)

I was biotin deficient ..,so I assume I had dysfunctional acety Co A? Felt like insulin resistance.

Definitely got an oxolate problem diagnosed by Susan Costen Owens. Review of testing going back to 2007 reviewed by Rich Van K shows sulfate wasting in urine, zinc , magnesium deficiency.

Electron transport chain was screwed .., proper copper..corrected that(empirical) RBC copper is normal.
So improved mito function?

G6DPH : curious about this? Not sure how to test?

Q: aren't all theses issues traceable back to oxolates?

Missing: heavy metals. If you don't have zinc or copper can't make metallotheineins.

 

[aquariusgirl]

Feels like Alzheimer's. Copper fungus in brain. Type 3 diabetes.

 

[Violeta]

Q: aren't all theses issues traceable back to oxolates?

Did someone tell you all these issues are traceable back to oxalates?

 

[Sam7777]

I would speculate that some assortment of gut microbiomes are responsible for ideal TUDCA metabolism. I don't know how the supplementation compares to the actual amount your body is suppose to make.

A few considerations though. One is that I have had pain, recurrent in my gallbladder, for about two years in a transient manner. I recently suspect that this is triggered by periods of hypersensitivity to food, namely amines in general, or certain immune stress, and that it is an issue with bile ejection/vagus nerve caused by vagus nerve dysfunction, similar to what I learned from Yasmina's interview with Driscoll. Like I said, I've gravitated to self medicating with cholinergic drugs for many years. Basically every choline type thing and everything like huperzine and cordycepts or schizandra or citicoline, I was interested in early on. I had a very hit and miss relationship with them, but there were periods I responded well.

I have these transient periods of gallbladder pain pretty much where I don't digest food well either, I can tell based on BM that something's not right with enough bile. But then it will go away, maybe a week, maybe two, a month, its strange in that manner. Since I did coffee enemas earlier in 2015, a lot of my constant hyper reaction and hyper fatigue lessened fairly considerably, for about I'd say 5 months. In some ways I am a bit improved since doing the coffee enemas, in some small symptoms, namely cold extremities and volatile moods. But doing these triggered what I now fairly presume are histamine related headaches. Now what's interesting is that I get these headaches when my immune system is particularly strained, and at the same time that the gallbladder flares up, and the hypersensitivity sets in, and the incomplete digestion and low bile function sets in.

I imagine gut microbes are extremely involved with histamine and bile metabolism. That paper I linked to is fairly descriptive about that. The articles seem to be a bit confused on what are good microbes though, ones that unconjugate bile acids vs conjugating them.

I would say some of these prescriptions like the one that caused your issues are clearly responsible for outright damage that taxes the body's need for the function of molecules like TUDCA. But it isn't a stretch to think that a lot of people already had terrible microbiomes and had poor TUDCA/ER/PUR protection to begin with, or very poor bile metabolism to begin with.

 

[mariovitali]

@Sam7777

May i ask how you got CFS?

 

[Sam7777]

Well I don't persay consider myself to have CFS, and I am a bit unsure whether CFS describes all the people who display the symptoms. But there really isn't any other community of illnesses that resembles my issues. It's actually fairly clear cut what's wrong with me, mercury. Unfortunately what really precipitated CFS like syndromes in me was incorrectly chelating mercury nearly 5 years ago. I respond very severely and strongly to any chelation treatment or anything that affects mercury toxicology and chemistry in the body. I've lost a lot of long and short term memory especially, and many of the symptoms caused by my initial incorrect procedure resemble the crashes that started many others CFS. I wouldn't be surprised if I had EBV or something along those lines, but since I never suspected CFS during my earlier years of seeking out answers I never got a lot of those types of tests. My mental symptoms strongly resemble CFS. No motivation, no memory, constant fog, time lapse, no concept of days and nights, or weeks or months really, can't consolidate memories or really structure in my life, or learn very well, basically what I would suspect if I had redistributed a ton of mercury into my brain and pummeled my immune system, which I did.

 

[mariovitali]

Dear All,


Just wanted to share a small update and some information which i feel is important.


I am continuing to have very positive effects, the latest being in myself as a person. No more ADHD, no more ups and downs in my Mood. Overall, i have never felt so well in my life.

My current regimen is :

Alpha GPC, Metafolin, Dibencozide, FMN, TUDCA, Selenium, P5P


Let's move now to the more important. The following information can be found in the following paper :

https://repositorio.uam.es/bitstream/handle/10486/12981/62321_Monsalve_Frontiers2012.pdf?sequence=1

@Valentijn i am mentioning you but i just want to make sure that you will not miss this post and give the paper a good read if you have the time.

Several studies have already assessed mitochondria as relevant organelles in the pathophysiology of liver cholestasis. Mitochondria are key components of the cholestatic liver diseases, being involved in several steps of the progression of the pathology. Overall mitochondrial function is reduced during experimental cholestasis, and this is associated with an important metabolic disturbance, characterized by reduced fatty acid oxidation and ketone body formation, both during short- and long-term cholestasis . Increased anaerobic glycolisis as a compensatory energy-producing mechanism in the cholestatic liver is associated with depletion of glycogen stores.

Hepatic GSH is depleted in long term cholestasis due to lower GSH synthesis and down-regulation of GSH
synthetic enzymes. During cholestasis, tumor necrosis factor alpha (TNF-a) and toxic bile acids have been involved in liver injury and hepatocyte apoptosis 68, 80. It is known that mitochondrial glutathione depletion sensitizes hepatocytes to apoptosis induced by TNF-a 105. In the long term cholestasis there is depletion of reduced glutathione (GSH) in liver mitochondria and consequently hepatocytes should be prone to cell death under this condition. Oxidative stress is especially marked in liver mitochondria in the long term experimental cholestasis, i.e. at 14 days after bile duct ligation or thereafter, as evidenced by a remarkable increase in lipid peroxidation and GSSG together with depletion of GSH. Furthermore, high-fat diets increased lipid oxidation in liver mitochondria and hepatic injury

and

Nrf2, nuclear factor erythroid derived 2 like 2 (Nrf2) is one of the transcription factors regulating inducible and
constitutive gene expression mediated by the antioxidant response elements (ARE), which are found in the promoter regions of two major detoxication enzymes, namely glutathione S-transferase A2 (GSTA2) and NADPH:quinone oxidoreductase (NQO1)

It is noteworthy that toxic bile acids induce a switch from Nrf2 to c-avian musculoaponeurotic fibrosarcoma/V-mafmusculoaponeurotic fibrosarcoma oncogene homolog G (c-Maf/MafG) ARE nuclear binding, leading to decreased expression of GSH synthetic enzymes and contributing to liver injury during chronic cholestasis. Ursodeoxycholic acid (UDCA) and S-adenosylmethionine treatment prevented this decrease preserving GSH levels and preventing liver injury . The beneficial effects of UDCA are mediated by activation of the PI3K/Akt/Nrf2 pathway.

Disorders that affect mitochondrial oxidative phosphorylation usually have an important impact on cellular metabolism, leading to liver diseases and often to multisystem alterations, and they have been called mitochondrial hepathopaties 136. They have been divided into primary disorders 137, 138, in which the mitochondrial defect is the primary cause of the liver disease, and secondary disorders that are caused either by genetic defects originally of non-mitochondrial proteins or by acquired injury to mitochondria

@Valentijn : Please recall how many posts have mentions on NRF2, ARE and NQO1 in this Thread. These Topics have been selected (among 487 Topics) several times from the Classification Algorithms i am using. Topics that have also been selected by the algorithm are Acetyl-coa, Mitochondrial Dysfunction, Acetylcholine, etc and were also discusssed here (and made sure that you were mentioned so you can tell me your opinion) : http://forums.phoenixrising.me/inde...e-treatment-for-cfs.37244/page-69#post-690688.


There is a Thread which discusses Mitochondrial damage, here in PR :


http://forums.phoenixrising.me/inde...drugs-which-cause-mitochondrial-damage.35742/


Moving on :

Compared with pre-treatment, UDCA was able to increase total and phosphorylated levels of Nrf-2. This was associated with an increase in the levels of thioredoxin (Trx) and thioredoxin reductase 1 (Trxr1), the only enzyme in charge of reducing Trx using NAPDH as a cofactor. These findings support previous experimental knowledge of an antioxidant effect of UDCA 18, 157. Thus, by this mechanism UDCA is suggested to protect mitochondria from oxygen radical-induced dysfunction. Other mechanisms through which UDCA ameliorates liver function in humans are yet to be established.

@all
I discussed numerous times in this Thread how a Liver Injury *may* have triggered our problems.


As i am finishing another round of Analysis i will post as soon as i have results.

 

[Sam7777]

http://forums.phoenixrising.me/inde...r-and-shade-protocol-cbs-sod-suox-bhmt.39799/

Yes, the grueling part is the killer. I have not looked at chelation therapy for over 10 years now because my detox systems are not working well enough.

For me, it was EBV that triggered my metabolic crash (in 1992). I'd had mercury in my teeth since the 1960s, but my detox systems were functioning, apparently, until after the crash.

Yes, I think the reduced L-glutathione cream triggered some mercury redistribution symptoms, but it took a while. The glutamate toxicity symptoms appeared first. I started it April 9th and took it off and on 5 days at a time. Dropped it like a hot potato July 27th.

Here's what I suspect: If I can get the glutathione redox system working, and the thiol redox system, I'll be able to tolerate thiols and sulfites and resume the methylation protocol. Then the mercury will detox the way it's supposed to. Peachy keen, hey?

Right now I'm thinking that the thiol redox system might be the upstream problem, and BTW, it affects glutathione recycling.

I'm pretty sure this is the strong suit of Christopher Shade's arguments. He talks about thioredoxin here. Fast forward to the 52:30 mark to jump right into this part in particular

I'm still learning about Shade and Cutler even 3 years later, its many layers deep. In fact you reminded me about thioredoxin. My theory that I speculate is that the enzyme systems are more important than supplements in conclusion. Yes you need supplements, but you need supplements that normalize all these enyzmes. Shade even says that its better to have higher GST enyzmes than it is to have high glutathione. It's kind of a principle really. It's the assembly line.

Though I might be slightly in error, I think most of what makes Shade's approach work is the bacopa, RLA, and triphala. Well those are what expel mercury, they're not his binder IMD. That's his approach in my crude terms.

I've been on the Cutler Protocol for 3-4 years, & on methylation protocols for a couple of years.

I've had modest but noticeable progress with chelation, & dramatic but erratic progress on the Freddd Protocol.

(You can see my protocols & SNPs below.)

My biggest roadblock with Cutler was massive thiol reactions - by far the worst (IMO) of anyone on the Frequent Dose Chelation forum. After half a year of incapacitation I began the Simplified Methylation Protocol, and these disappeared in a few days - never to return. The SMP didn't have methyl B12, so I surmise that the methyl-folate is what did the trick.

I've only heard of one or two others who fixed the thiol problem this way - tho possibly few try it, as Cutler is very skeptical about methylation protocols. (Cults tend to form around illnesses & healing methods. I agree with you that no-one is totally correct. Tho I do tend to trust Cutler on ALA over RLA, as he has more science in his head on heavy metal transport than anyone, so far as I can tell.)

Now I'm on the Freddd protocol. I am learning dosing the hard way, but the improvements are great so long as they last. Then I crash, ramp up folate & tweak down carnitine (or whatever), improve again...

Methylfolate is also part of the Freddd Protocol, & I am able to chelate with ALA at 300 mg/dose now. I dose two-hourly - a faster way to burn through the mercury IMO.

@stridor much improved his ability to chelate, & had big health gains, after beginning methylation therapy.

I don't have his scientific knowledge, nor yours. I just try to find the smartest person in the room on a given subject, & do what they say. Then I tweak a lot based on what happens, or doesn't.

For practical purposes I regard pyroluria as a separate subject, but have this year seen anxiety evaporate after beginning the zinc, B6, etc.

@picante , I think you're right about thioredoxin being the upstream problem for thiol issues. I have been having severe reactions to isothiocyanate, it just kept getting worse and worse. I started taking FMN about two weeks ago, and then about a week ago decided to try broccoli and cauliflower. I did get one of the symptoms I get from isothiocyanates, abdominal pain, and was trying different things to get rid of it. I was going to try clay and charcoal, but before I took them I took another dose of FMN, and voila, then pain in my abdomen subsided. I started taking more doses of FMN, even when I wake up during the night or get a headache, a full 25mg after eating broccoli and cauliflower, and I think I am getting over the problem.

I had been taking B2 for about a year and a half now, but have noticed that the coenzymated form works much better for me. (I hope I am not incorrect about FMN being very important for thioredoxin synthesis.)

This weekend I will try eating eggs again.

It would be great to be able to eat vegetables again, especially after finding this link.

Sulforaphane Suppresses Oligomerization of TLR4 in a Thiol-Dependent Manner
http://www.jimmunol.org/content/184/1/411

TLRs are pattern recognition receptors that detect invading microorganisms and nonmicrobial endogenous molecules to trigger immune and inflammatory responses during host defense and tissue repair. TLR activity is closely linked to the risk of many inflammatory diseases and immune disorders. Therefore, TLR signaling pathways can provide efficient therapeutic targets for chronic diseases. Sulforaphane (SFN), an isothiocyanate, has been well known for its anti-inflammatory activities. In this study, we investigated the modulation of TLR activity by SFN and the underlying mechanism. SFN suppressed ligand-induced and ligand-independent TLR4 activation because it prevented IL-1R–associated kinase-1 degradation, activation of NF-κB and IFN regulatory factor 3, and cyclooxygenase-2 expression induced by LPS or overexpression of TLR4. Receptor oligomerization, which is one of the initial and critical events of TLR4 activation, was suppressed by SFN, resulting in the downregulation of NF-κB activation. SFN formed adducts with cysteine residues in the extracellular domain of TLR4 as confirmed by liquid chromatography-tandem mass spectrometry analysis and the inhibitory effects of SFN on oligomerization and NF-κB activation were reversed by thiol donors (DTT and N-acetyl-L-cysteine). These suggest that the reactivity of SFN to sulfhydryl moiety contributes to its inhibitory activities. Blockade of TLR4 signaling by SFN resulted in the reduced production of inflammatory cytokines and the decreased dermal inflammation and edema in vivo in experimental inflammatory animal models. Collectively, our results demonstrated that SFN downregulated TLR4 signaling through the suppression of oligomerization process in a thiol-dependent manner. These present a novel mechanism for beneficial effects of SFN and a novel anti-inflammatory target in TLR4 signaling.

How do you know your reaction is to isothiocyanate? What are you actually ingesting when you get these severe reactions?



I am still confused about synthesis of thioredoxin itself (Trx). This book, Advanced Nutrition and Human Metabolism, says that thioredoxin reductase is a flavoprotein, and the chart on page 328 shows both riboflavin (FAD) and niacin (NADPH) involved in its [activity? synthesis? I'm not sure which].

Clearly, the FMN is doing something for you. I'm taking R-5'-P (Douglas Labs), which is allegedly the same chemical, because I wasn't tolerating something in the sublingual FMN. But I'm now taking 1/2 cap (5 mg) 3-4 X a day, because when I take the whole cap, I get pretty uncomfortable hot flashes (no doubt it's ramping up my cellular thyroid metabolism).

Another piece, though, is niacin. I've been gradually increasing my niacinamide supplementation since learning that niacin provides the main cofactor, NADPH, for the reduction of thiols. And FAD seems to be involved somehow in NADPH recycling (???).

I'm tolerating an egg most days now, and a mid-sized serving of Swiss chard.

No, I read fairly extensively in the archives of peoples discussions here to see about BH4. I am skeptical of such an approach because it's essentially throwing an end product into the cycle (that's almost impossible to afford or obtain) without fixing the underlying reasons its low. So I am pretty convinced I have to trudge through Cutler, but am obviously trying to do everything I can to speed it up and make it more bearable, in the hopes that these sorts of snps correct themselves somewhat. Of course it is confusing comparing to people here. Almost everyone here responds to methyl b12 and methyl folate, but I don't. And I have a special history with Hg/amalgam/cutler, I AM one of the unlucky people who blasted themselves with an improper protocol and never was right again, I did do a ton of damage, basically sticking it all in my brain a fair bit. These are the individual things that make it hard to gauge. I really do think Shade is right about people having totally shut down enzyme systems, multiple enzyme systems interacting with one another, and also being affected by these kinds of snps.

Of course, I was very surprised at just how strongly some of those people responded to BH4, at least initially, but I think that wears out over time, it balances things out some, then since the snps are still there and the root issues are still there it gets deficient again, ad naseum presumably. If I am not mistaken one thing suggested for BHMT was the TMG and malic acid. I tried malic acid but didn't respond. I might only get very mild benefits from TMG.

I am tempted to say that even with people who don't have amalgam illness there's a compelling reason to try maybe up to a gram of RLA a day, especially after reading on it, and with Shade. I mean in terms of someone suspecting thioredoxin. Course' the risk in that is assuming you don't have amalgam illness, which is a mistake I have made. But for instance, it's well established that lipoic generally treats the damage caused by lead while not persay chelating lead much. I think that there's quite a host of things that could have the ability to smash the methylation cycle. Smashing it the way mercury does, at least to a degree. The same sort of inflammation that messes these enzymes up. There are countless persistent organic pollutants, plus cadmium, arsenic, etc. RLA is still very important for this I believe.

I think it is really important to kind of assume that there's something latent (some pollutant) triggering significant enough inflammation to affect things. The malic acid idea made more sense because it was further upstream, and the premise is to try to get the glutathione system up by raising BH4 (the GSH GST etc enzymes specifically). But producing more glutathione doesn't even neccesarily guarentee that those enzymes are being raised.

There is the mushroom cordyceps that is suppose to affect NO levels in the body, and I've had OK results once in the past. But I can't say the effects lasted, primarily because of my redistribution accident and Hg. With cordyceps I guess the issue is only $$, (which cheaper brands aren't too bad, typical herb, nothing compared to BH4).

Like for instance, comparing RLA to cordyceps, I think cordyceps runs its course pretty early. Adaptogens don't just keep these biochemical changes going forever, it takes about six weeks, there are some lasting changes, but then you develop tolerance to the herb early on, and you kind of have to wait several months. But RLA is much more . . persistently pharmaceutical.

I've recently found this study, which was in vitro, looking at the effects of mercury compounds on glutaredoxin and thioredoxin: Inhibition of the human thioredoxin system. A molecular mechanism of mercury toxicity.


This study is similar: Biomarkers of Adverse Response to Mercury: Histopathology versus Thioredoxin Reductase Activity


[In this quote I changed "on" to "in" because it's a grammatical error that could cause confusion. And I'm a compulsive editor.]

 

[Sam7777]

I've grudged through a little half of this seventy page thread. Mario and Valentijn you both make some good points. I suppose I remain doubtful about how snps work and in the dark since ive not done the test.

That being said some things seem odd. Namely that people seem to develop these mthfr snp issues in response to liver stress of a varieties of sorts. For instance you would see this more specifically in people who have measueable biomarkers associated with common industrial disease. Basically by the time someone has high cpr or homocysteine oe bad lipids or insulin resistance or any type of abdominal excess weight or nafld you would see the mitochondrial damage and alteration of glutathione metabolism in the liver.

What I dont quite understand about these snps is why they seem harmless until some environmental shift.

For instance Valentijn , Cutler is at least as skeptical towards snps as you. He really hates snps industry. However he says that if the mercury is taken out the snps cease to be a problem. At least one admin to cutlers forum stridor was able to only finish chelation with fredds protocol.

Is it that perhaps as in the case of APOE4 some alleles are just easier to 'overload' with external stress?

The problem in this case and what i see in this thread and in shades work is that there are a number of points in phase 1 & 2 pathways as mario mentioned where other snps alleles could go awry. And not just methylation. Problem is ofcourse we dont know which or if. But logically it doesnt seem like you wouldonly havemethyylation issues and escape unscathed inother key detox genes and haplotypes.

Mario i recommend youtube and shades website and quicksilver facebook group to see these videos of his explaining hg detox. And also the video I quoted above.

Shades protocol unlike cutlers is basically aimed at the gsh system. Its meant to detox and repair liver damage. If you troll pubmed youll see quickly how associated r lipoic and alpha lpoic acid are associated with liver disease and how similiar themechanisms are to tudca. The main thing shades protocol does is upregulate nrf2. This is what he and chris turf will tell you. Shade uses rla as a gene regulater and cutler uses ala as a chelator. But rla in people without merc issues is a potent regenerative antioxidant for the liver. Ive always noted how lipoic seems to affect the bile metabolism in the literature.

Im still looking for and angle of making probiotics help me produce tudca. What i will say is that homemade kefir has greatly helped with bile flow and digestion.

I suspect i have a choline and fmn deficiency. I know i stoppwd eating eggs in august and thats when things started getting worse with histamine and thiols.

What Im worried about now are the rammification of these ghost snps affecting phase two in regards to diet. I think this is especiall problematic because of how the food regulates genes. You mentioned that high fat diets increase liver oxidation. Well my observations have led me to note people seem to have issue with histamine arachidonic acid omega six saturated fat sulfite sulfate thiol and especially lectins. I personally only evr thrived on a pesco paleo intermittant fasting diet. But Im beginning to wonder about the merits of a fuhrman type vegan low fat diet. A low fat paleo vegan diet would truly be awful but maybe this is why so many recover being a raw vegan fruitarian. Maybe it turns off these genes and lets the liver repair while bile acid salt metabolism normalizes. Right now in the most general sense and survey of literature the standard american diet seems suicidal compared to some choline probiotic rich high fiber low fat african diet. But these cultures dont seem to have the same issues with lectins...

 

[Valentijn]

What I dont quite understand about these snps is why they seem harmless until some environmental shift.

There are a few different concepts here. One is strict genetics - what the SNPs do. Every set of three consecutive SNPs (a codon) on an exome in a gene spell out amino acids that connect to each other to create a protein. You can read codons likes words in a book.

Another is genetic expression. Things like methylation can cause some genes to be expressed more or less, or have a methyl group attached.

And then there is the interaction of genetic products with other genetic products and external factors. This is sometimes discussed in the context of the genes involved, but isn't really a genetic issue, and often the actual SNPs (genetic code) don't matter at all. In this case, the SNPs are actually harmless, and the real problem is with an externally triggered disease process.

What we've seen from Yasko is a lot of strict SNP claims which turned out to be obvious BS. Some people then moved to assuming that there must be some mechanism involving genetic expression which causes these irrelevant SNPs to suddenly become relevant. But that is 100% speculation, and very unlikely.

If mercury caused extremely common CBS SNPs to result in some pathological reaction when exposed to low levels of mercury, for example, the research would have shown at least some increased risk due to the huge reaction from everyone with mercury fillings. Similarly, doctors, orthodontists, and patients themselves would notice that most of them get extremely sick due to mercury fillings. Neither of those things have happened.

So my general view regarding genetic expression is that it is a real thing and can happen. But it's also completely ridiculous to assume that it's happening in any particular case, and that it's happening in an extreme manner which is completely contrary to the existing research regarding that SNP. And without the relevant research it's just baseless speculation, and is no more likely to result in a correct result than astrology or reading tarot cards (or a random number generator).

 

[mariovitali]

In a nutshell this Thread makes the following hypotheses :


a) CFS, Post-Finasteride Syndrome, Fibromyalgia, Gulf war syndrome, Post-Accutane syndrome (and other Syndromes discussed here) have the same basis as a cause : Liver injury/Gene downregulation which leads to a degree of Cholestasis and/or impaired intrahepatic circulation. This leads to further Liver injury and the body falls to a vicious cycle.

b) It appears that problems in Bile Acid homeostasis have very important Health Implications

c) Methylation is only a small part of the solution. This is why the majority of people that have tried it, got some benefits instead of a cure.

d) SNPs have to be looked in a more holistic way. Interaction of SNPs has to be looked at. As an example, the combination -i repeat : THE COMBINATION- of JUST NAT2 SNPs predicts slow vs intermediate vs fast Acetylator Phenotypes (using a Machine Learning Method called SVM) :

http://nat2pred.rit.albany.edu/help.html

N-acetyltransferase-2 (NAT2) is an enzyme that catalyzes the acetylation of aromatic and heterocyclic amine carcinogens. Because of its involvement in the detoxification of carcinogens, mutations within NAT2 that affect the enzymatic acetylator activity may also modify risk of cancer development. It was shown that individuals in human populations are divided into three enzymatic acetylator phenotypes: slow, rapid, and intermediate. A number of single nucleotide polymorphisms (SNPs) within the NAT2 gene have been found to affect the NAT2 acetylator phenotype. This web-server implements Support Vector Machine (SVM), a supervised pattern recognition method, to infer the NAT2 acetylator phenotype from six SNPs found in the NAT2 gene in positions 282, 341, 481, 590, 803, and 857. Given a combination of these SNPS observed in a particular individual (i.e., his/her genotype), the web-server assigns one of the three NAT2 phenotypes, slow, intermediate, or rapid, to this individual. The web-server can be used for a fast determination of the NAT2 acetylator phenotype in genetic screens. NAT2PRED was developed on a dataset where majority of subjects are Caucasian (94%, see Table 1). However, the model utilizes a generally observed linkage disequilibrium between the six NAT2 SNPs and performs very well on other ethnic groups (for the results of an independent critical evaluation of NAT2PRED conducted using a worldwide dataset composed of 56 populations please refer to Sabbagh et al, 2009, BMC Medical Genetics).

e) There is a clear pattern of several SNPs in the DNA Samples that i analyzed that have to do with Bile Acids Homeostasis and the FXR receptor. Of course i do not have any controls but there are some indications (so i am not making ANY statement) that people with the most severe symptoms have many SNPs at specific genes (such as CYP7A1, NR1H4). The more problems exist in these Genes -among others- the more severe the Symptoms :

 

[mariovitali]

FYI : Accutane = 13-cis-Retinoic Acid



@Needinghelp Do you get my point?

@Valentijn **Please** make a note of AKR1D1, CYP7A1, CYP8B1, FXR (NR1H4) which is discussed below...Thank you.

All-trans retinoic acid regulates hepatic bile acid homeostasis.
Yang F1, He Y2, Liu HX3, Tsuei J4, Jiang X5, Yang L6, Wang ZT7, Wan YJ8.
Author information

Abstract
Retinoic acid (RA) and bile acids share common roles in regulating lipid homeostasis and insulin sensitivity. In addition, the receptor for RA (retinoid x receptor) is a permissive partner of the receptor for bile acids, farnesoid x receptor (FXR/NR1H4). Thus, RA can activate the FXR-mediated pathway as well. The current study was designed to understand the effect of all-trans RA on bile acid homeostasis. Mice were fed an all-trans RA-supplemented diet and the expression of 46 genes that participate in regulating bile acid homeostasis was studied. The data showed that all-trans RA has a profound effect in regulating genes involved in synthesis and transport of bile acids. All-trans RA treatment reduced the gene expression levels of Cyp7a1, Cyp8b1, and Akr1d1, which are involved in bile acid synthesis. All-trans RA also decreased the hepatic mRNA levels of Lrh-1 (Nr5a2) and Hnf4α (Nr2a1), which positively regulate the gene expression of Cyp7a1 and Cyp8b1. Moreover, all-trans RA induced the gene expression levels of negative regulators of bile acid synthesis including hepatic Fgfr4, Fxr, and Shp (Nr0b2) as well as ileal Fgf15. All-trans RA also decreased the expression of Abcb11 and Slc51b, which have a role in bile acid transport. Consistently, all-trans RA reduced hepatic bile acid levels and the ratio of CA/CDCA, as demonstrated by liquid chromatography-mass spectrometry. The data suggest that all-trans RA-induced SHP may contribute to the inhibition of CYP7A1 and CYP8B1, which in turn reduces bile acid synthesis and affects lipid absorption in the gastrointestinal tract.

 

[Sam7777]

What i specifically wanna know Val is what you believe is causing methylation disorders. Do you consider fredd and vanks method to be a case of dealing with a gene expression problem where there are not enough methyl donors to make those mthfr alleles fuction correctly?

I am considerably concerned with what manifests these methlyation conditions

I dont neccesarily think the snps are the bottom thing to look at either. But the amount of speculation on my part comes from being in these chronic health communities for many years, and yes there is a very large community of people reporting issues with amalgams and recovering with chelation. The medical and legal burden is as much on the system to disprove all of those people and frankly they havent, not that it matters given the legal environment but never the less I take the word of the the extent communities (including this one) over the journals.

I think frankly in so far as we are talking about latent exposure to regulated chems that looking at gene expression is high on the order. The reason Im interested in this forum Mario is because I have also noticed very similar trends among disparate groups. Methylation and endocrine disease and some autoimmune conditions come up frequently with many people Ive encountered who had injury from pharmaceuticals. Ive noticed in Lymes and hep c and ebv and mold exposure cases (mold is arguably the worst).

There are a lot of pathways to break down besides methylation and that makes the concern of some issue with gene expression more likely if you are in fact dealing with weakened pathways not functioning on a molecular level as adequately.

Ive yet to get a straight answer out of cutler shade or other groups but alot of those people in those groups are worried about bad gene expression.

Im probably going to have to look at some environmental health journals. I suggest that as well mario. Maybe some papers studying benzene or hydro carbon effects on gene expression just to conceptualize.

 

[Valentijn]

The more problems exist in these Genes -among others- the more severe the Symptoms

Except you're guessing that pretty much everything is a problem. It isn't, and the very high Minor Allele Frequency should be a good hint that it isn't.